Predicting Transfer Fee of a Football Player

"In 2019, the football transfer market reached unprecedented levels both in terms of the number of transfers and the amount spent on fees.."

James Kitching,Director of Football Regulator

Growing football industry can cause clubs spend higher than what they possibly win. UEFA brought out Financial Fair Play Regulations to audit the expenses of clubs and prevent them to collapse financially.UEFA explained those regulations as improving the overall financial health of European club football.To follow the rules in the regulation, valuation of a player becomes crucial either to sell or to buy.

Fifa published a report in 2019, showing the statistics about transfers in 2019. In the report, it is highlighted many times that football teams can give lots of money to be in the competition with others.

Spending on transfer fees by year (USD billion)

Above chart shows how fast the football transfer industry is growing.It reached ~7.5 billion USD in 2019.

Number of transfers with fees and average transferfee by year (USD billion)

Above table shows the numbers of transfers are increasing, average fees are increasing as well as years pass.

What makes a football player expensive? Can the fee be predicted? I decided to go on these questions and by using the world-wide known website "transfermarkt" I built a model on transfer fees. I started firstly scraping transfer data from the transfermarkt

Web Scraping and Feature Engineering

I decided to scrape all the transfers with fee,player profile all the matches a football player played before transfer date, achievements and player transfer history using Beautifusoup. All detailed scraping codes can be reachable in my github repository

Below I will reason behind scraping specific link and the features i produced after those scraping codes.

Transfers

Transfers are the main table in which there are all the transfer history of all leagues that transfermarkt has. I decided to scrape all the transfers from the link. This link shows the transfers in each date as shown below.

I looped from all the pages and dates from 2016 to 2020. Finally i eliminated loans & Free transfers to get paid transfers. Data pattern of transfer data is :

import pandas as pd
pd.set_option('max_info_columns', 500)
transfers =  pd.read_pickle('C:/Users/YAVUZ/Transfer Fee Project/0.Web Scraping/0.Transfers/Paid_Transfers_2016_2020.pkl')
transfers.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 9499 entries, 0 to 294176
Data columns (total 14 columns):
 #   Column           Non-Null Count  Dtype 
---  ------           --------------  ----- 
 0   Transfer_Link    9499 non-null   object
 1   Transfer_id      9499 non-null   object
 2   Transfer_Date    9499 non-null   object
 3   Page_Number      9499 non-null   object
 4   id               9499 non-null   object
 5   Link             9499 non-null   object
 6   Player_Name      9499 non-null   object
 7   Player_Position  9499 non-null   object
 8   Age              9499 non-null   object
 9   Club_Left        9499 non-null   object
 10  League_Left      9499 non-null   object
 11  Club_Joined      9499 non-null   object
 12  League_Joined    9499 non-null   object
 13  Transfer_Fee     9499 non-null   object
dtypes: object(14)
memory usage: 1.1+ MB

Transfer Details and Teams Played

Transfer details are the source of the transfer history of a player. Also in each transfer, specific info is provided such as age at the time of transfer, market value at the time of transfer, remaining contract .The transfer detail website for a player can be reached from here.

I looped for all the players in paid transfer dataset.I also created some other features like Number of transfers in transfer history, Avg Market Value, Total Fee, Avg Fee etc. I also created flag features such as: Country_Change_Flag, League_Change_Flag,League_Tier_Up_Flag,League_Tier_Down_Flag

I also created another dataset which shows the team a player played in each date.

Data patterns of transfer detail and team played datasets are :

transfer_detail =  pd.read_pickle('C:/Users/YAVUZ/Transfer Fee Project/0.Web Scraping/1.Transfer Details/Transfers_Hst_Detail2.pkl')
transfer_detail.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 9499 entries, 0 to 9498
Data columns (total 26 columns):
 #   Column                             Non-Null Count  Dtype 
---  ------                             --------------  ----- 
 0   Transfer_Link                      9499 non-null   object
 1   Transfer_id                        9499 non-null   object
 2   id                                 9499 non-null   object
 3   NOF_Transfers                      9499 non-null   object
 4   Avg_Market_Value                   7729 non-null   object
 5   Tot_Fee_Loan_Fee_Exc               9499 non-null   object
 6   Avg_Fee                            4166 non-null   object
 7   Tot_Fee_Loan_Fee_Inc               9499 non-null   object
 8   Age_at_Time_of_transfer            9499 non-null   object
 9   Contract_Left_at_Time_of_transfer  7496 non-null   object
 10  Market_Value_at_Time_of_transfer   9499 non-null   object
 11  Team_Left_Tier                     9447 non-null   object
 12  Team_Joined_Tier                   9447 non-null   object
 13  Team_Left_League                   9447 non-null   object
 14  Team_Joined_League                 9447 non-null   object
 15  Fee                                9499 non-null   object
 16  Transfer_Season                    9499 non-null   object
 17  Transfer_Date                      9499 non-null   object
 18  Team_Left                          9499 non-null   object
 19  Team_Joined                        9499 non-null   object
 20  Country_Left                       9141 non-null   object
 21  Country_Joined                     9371 non-null   object
 22  Country_Change_Flag                9499 non-null   object
 23  League_Change_Flag                 9499 non-null   object
 24  League_Tier_Up_Flag                9499 non-null   object
 25  League_Tier_Down_Flag              9499 non-null   object
dtypes: object(26)
memory usage: 1.9+ MB

team_played =  pd.read_pickle('C:/Users/YAVUZ/Transfer Fee Project/0.Web Scraping/1.Transfer Details/Team_played_All.pkl')
team_played.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 84748 entries, 0 to 84747
Data columns (total 7 columns):
 #   Column         Non-Null Count  Dtype         
---  ------         --------------  -----         
 0   Team           84748 non-null  object        
 1   Start          84748 non-null  datetime64[ns]
 2   End            75250 non-null  datetime64[ns]
 3   Transfer_Link  84748 non-null  object        
 4   Transfer_id    84748 non-null  object        
 5   id             84748 non-null  object        
 6   Transfer_Date  84748 non-null  object        
dtypes: datetime64[ns](2), object(5)
memory usage: 4.5+ MB

Player Profile

Player profile is providing the general information about the footballer such as citizenship, height,preferred foot, positions etc. You can reach a player's profile page from here. Below screenshot is showing available information about a player's profile.

The data pattern for profile is:

#loading player profile  features from pkl
profile=pd.read_pickle('C:/Users/YAVUZ/Transfer Fee Project/0.Web Scraping/2.Player_Profiler/Player_profile.pkl')
profile.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 9499 entries, 0 to 9498
Data columns (total 13 columns):
 #   Column           Non-Null Count  Dtype 
---  ------           --------------  ----- 
 0   Transfer_Link    9499 non-null   object
 1   Transfer_id      9499 non-null   object
 2   id               9499 non-null   object
 3   Transfer_Date    9499 non-null   object
 4   Date_of_birth    9499 non-null   object
 5   Place_of_birth   9499 non-null   object
 6   Height           9499 non-null   object
 7   Citizenship      9499 non-null   object
 8   Position         9499 non-null   object
 9   Foot             9499 non-null   object
 10  Main_position    9499 non-null   object
 11  other_position1  9499 non-null   object
 12  other_position2  9499 non-null   object
dtypes: object(13)
memory usage: 964.9+ KB

Stats in Club Matches

This was the hard part of the project. In transfermarkt, stats are given in each season, however a footballer can change his club during the season. Since I wanted to get the stats before the transfers, I could not use the stats of website, so i decided to create my own features by scraping all the matches a footballer played. The scraping code is available in github, however dataset is not available, since it's bigger than github's limit.The matches are available in the link

Later I created features like , how many times of a player played,avg minutes, goals, assists, benched times, substituted games,injuries,suspensions,match points, etc in last 5,10,20,30 games before transfer date.. To do this i firstly worked on "WinLoseDraw.ipynb" to get win/draw or lose information. Then I created features in "Stats_Features.ipynb" in feature engineering folder.

The data pattern of stats features datasets is:

stats = pd.read_pickle('C:/Users/YAVUZ/Transfer Fee Project/1.Feature Engineering/Stats_Features_All.pkl')
stats.info()

<class 'pandas.core.frame.DataFrame'>
Index: 9381 entries, 3105419 to 1115385
Data columns (total 200 columns):
 #   Column                                       Non-Null Count  Dtype          
---  ------                                       --------------  -----          
 0   Date_30                                      9381 non-null   int64          
 1   starting_lineup_30                           9381 non-null   int32          
 2   matches_played_flag_30                       9381 non-null   int32          
 3   Goals_30                                     9381 non-null   float64        
 4   Assists_30                                   9381 non-null   float64        
 5   Own goals_30                                 9381 non-null   float64        
 6   yellow_card_flag_30                          9381 non-null   int32          
 7   second_yellow_card_flag_30                   9381 non-null   int32          
 8   red_card_flag_30                             9381 non-null   int32          
 9   Minutes played_30                            9381 non-null   float64        
 10  substitution_off_flag_30                     9381 non-null   int32          
 11  match_played_rate_30                         9381 non-null   float64        
 12  rate_subs_off_30                             9208 non-null   float64        
 13  match_points_played_30                       9282 non-null   float64        
 14  match_points_notplayed_30                    9098 non-null   float64        
 15  total_goals_team_30                          9287 non-null   float64        
 16  total_goals_team_played_30                   9002 non-null   float64        
 17  total_goals_team_conceded_30                 9287 non-null   float64        
 18  total_goals_team_conceded_played_30          9002 non-null   float64        
 19  clean_sheet_flg_played_30                    9282 non-null   float64        
 20  clean_sheet_flg_notplayed_30                 9098 non-null   float64        
 21  lineup_rate_30                               9282 non-null   float64        
 22  minutes_per_game_30                          9282 non-null   float64        
 23  goals_per_Game_30                            9282 non-null   float64        
 24  assists_per_game_30                          9282 non-null   float64        
 25  own_goals_per_game_30                        9282 non-null   float64        
 26  yellow_cards_per_game_30                     9282 non-null   float64        
 27  second_yellow_card_per_game_30               9282 non-null   float64        
 28  red_card_per_game_30                         9282 non-null   float64        
 29  team_goals_per_game_30                       9002 non-null   float64        
 30  points_per_game_30                           9282 non-null   float64        
 31  team_conceeded_goals_per_game_30             9002 non-null   float64        
 32  clean_sheet_per_game_30                      9282 non-null   float64        
 33  team_goals_per_game_not_played_30            8724 non-null   float64        
 34  clean_sheet_per_game_not_played_30           9098 non-null   float64        
 35  team_conceeded_goals_per_game_not_played_30  8724 non-null   float64        
 36  points_per_game_not_played_30                9098 non-null   float64        
 37  minutes_played_coverage_played_30            9282 non-null   float64        
 38  minutes_played_coverage_all_30               9381 non-null   float64        
 39  points_played_coverage_30                    9282 non-null   float64        
 40  points_not_played_coverage_30                9098 non-null   float64        
 41  Injury_30                                    2108 non-null   float64        
 42  Suspension_30                                2218 non-null   float64        
 43  not in squad_30                              7288 non-null   float64        
 44  on the bench _30                             6088 non-null   float64        
 45  injury_rate_30                               2108 non-null   float64        
 46  suspension_rate_30                           2218 non-null   float64        
 47  on_the_bench_rate_30                         6088 non-null   float64        
 48  not_in_squad_rate_30                         7288 non-null   float64        
 49  last_played_game_recency_30                  9381 non-null   timedelta64[ns]
 50  Date_20                                      9381 non-null   int64          
 51  starting_lineup_20                           9381 non-null   int32          
 52  matches_played_flag_20                       9381 non-null   int32          
 53  Goals_20                                     9381 non-null   float64        
 54  Assists_20                                   9381 non-null   float64        
 55  Own goals_20                                 9381 non-null   float64        
 56  yellow_card_flag_20                          9381 non-null   int32          
 57  second_yellow_card_flag_20                   9381 non-null   int32          
 58  red_card_flag_20                             9381 non-null   int32          
 59  Minutes played_20                            9381 non-null   float64        
 60  substitution_off_flag_20                     9381 non-null   int32          
 61  match_played_rate_20                         9381 non-null   float64        
 62  rate_subs_off_20                             9046 non-null   float64        
 63  match_points_played_20                       9180 non-null   float64        
 64  match_points_notplayed_20                    8747 non-null   float64        
 65  total_goals_team_20                          9268 non-null   float64        
 66  total_goals_team_played_20                   8759 non-null   float64        
 67  total_goals_team_conceded_20                 9268 non-null   float64        
 68  total_goals_team_conceded_played_20          8759 non-null   float64        
 69  clean_sheet_flg_played_20                    9180 non-null   float64        
 70  clean_sheet_flg_notplayed_20                 8747 non-null   float64        
 71  lineup_rate_20                               9180 non-null   float64        
 72  minutes_per_game_20                          9180 non-null   float64        
 73  goals_per_Game_20                            9180 non-null   float64        
 74  assists_per_game_20                          9180 non-null   float64        
 75  own_goals_per_game_20                        9180 non-null   float64        
 76  yellow_cards_per_game_20                     9180 non-null   float64        
 77  second_yellow_card_per_game_20               9180 non-null   float64        
 78  red_card_per_game_20                         9180 non-null   float64        
 79  team_goals_per_game_20                       8759 non-null   float64        
 80  points_per_game_20                           9180 non-null   float64        
 81  team_conceeded_goals_per_game_20             8759 non-null   float64        
 82  clean_sheet_per_game_20                      9180 non-null   float64        
 83  team_goals_per_game_not_played_20            8133 non-null   float64        
 84  clean_sheet_per_game_not_played_20           8747 non-null   float64        
 85  team_conceeded_goals_per_game_not_played_20  8133 non-null   float64        
 86  points_per_game_not_played_20                8747 non-null   float64        
 87  minutes_played_coverage_played_20            9180 non-null   float64        
 88  minutes_played_coverage_all_20               9381 non-null   float64        
 89  points_played_coverage_20                    9180 non-null   float64        
 90  points_not_played_coverage_20                8747 non-null   float64        
 91  Injury_20                                    1652 non-null   float64        
 92  Suspension_20                                1745 non-null   float64        
 93  not in squad_20                              6358 non-null   float64        
 94  on the bench _20                             4990 non-null   float64        
 95  injury_rate_20                               1652 non-null   float64        
 96  suspension_rate_20                           1745 non-null   float64        
 97  on_the_bench_rate_20                         4990 non-null   float64        
 98  not_in_squad_rate_20                         6358 non-null   float64        
 99  last_played_game_recency_20                  9381 non-null   timedelta64[ns]
 100 Date_10                                      9381 non-null   int64          
 101 starting_lineup_10                           9381 non-null   int32          
 102 matches_played_flag_10                       9381 non-null   int32          
 103 Goals_10                                     9381 non-null   float64        
 104 Assists_10                                   9381 non-null   float64        
 105 Own goals_10                                 9381 non-null   float64        
 106 yellow_card_flag_10                          9381 non-null   int32          
 107 second_yellow_card_flag_10                   9381 non-null   int32          
 108 red_card_flag_10                             9381 non-null   int32          
 109 Minutes played_10                            9381 non-null   float64        
 110 substitution_off_flag_10                     9381 non-null   int32          
 111 match_played_rate_10                         9381 non-null   float64        
 112 rate_subs_off_10                             8523 non-null   float64        
 113 match_points_played_10                       8868 non-null   float64        
 114 match_points_notplayed_10                    7658 non-null   float64        
 115 total_goals_team_10                          9261 non-null   float64        
 116 total_goals_team_played_10                   8149 non-null   float64        
 117 total_goals_team_conceded_10                 9261 non-null   float64        
 118 total_goals_team_conceded_played_10          8149 non-null   float64        
 119 clean_sheet_flg_played_10                    8868 non-null   float64        
 120 clean_sheet_flg_notplayed_10                 7658 non-null   float64        
 121 lineup_rate_10                               8868 non-null   float64        
 122 minutes_per_game_10                          8868 non-null   float64        
 123 goals_per_Game_10                            8868 non-null   float64        
 124 assists_per_game_10                          8868 non-null   float64        
 125 own_goals_per_game_10                        8868 non-null   float64        
 126 yellow_cards_per_game_10                     8868 non-null   float64        
 127 second_yellow_card_per_game_10               8868 non-null   float64        
 128 red_card_per_game_10                         8868 non-null   float64        
 129 team_goals_per_game_10                       8149 non-null   float64        
 130 points_per_game_10                           8868 non-null   float64        
 131 team_conceeded_goals_per_game_10             8149 non-null   float64        
 132 clean_sheet_per_game_10                      8868 non-null   float64        
 133 team_goals_per_game_not_played_10            6451 non-null   float64        
 134 clean_sheet_per_game_not_played_10           7658 non-null   float64        
 135 team_conceeded_goals_per_game_not_played_10  6451 non-null   float64        
 136 points_per_game_not_played_10                7658 non-null   float64        
 137 minutes_played_coverage_played_10            8868 non-null   float64        
 138 minutes_played_coverage_all_10               9381 non-null   float64        
 139 points_played_coverage_10                    8868 non-null   float64        
 140 points_not_played_coverage_10                7658 non-null   float64        
 141 Injury_10                                    1042 non-null   float64        
 142 Suspension_10                                1064 non-null   float64        
 143 not in squad_10                              4910 non-null   float64        
 144 on the bench _10                             3552 non-null   float64        
 145 injury_rate_10                               1042 non-null   float64        
 146 suspension_rate_10                           1064 non-null   float64        
 147 on_the_bench_rate_10                         3552 non-null   float64        
 148 not_in_squad_rate_10                         4910 non-null   float64        
 149 last_played_game_recency_10                  9381 non-null   timedelta64[ns]
 150 Date_5                                       9381 non-null   int64          
 151 starting_lineup_5                            9381 non-null   int32          
 152 matches_played_flag_5                        9381 non-null   int32          
 153 Goals_5                                      9381 non-null   float64        
 154 Assists_5                                    9381 non-null   float64        
 155 Own goals_5                                  9381 non-null   float64        
 156 yellow_card_flag_5                           9381 non-null   int32          
 157 second_yellow_card_flag_5                    9381 non-null   int32          
 158 red_card_flag_5                              9381 non-null   int32          
 159 Minutes played_5                             9381 non-null   float64        
 160 substitution_off_flag_5                      9381 non-null   int32          
 161 match_played_rate_5                          9381 non-null   float64        
 162 rate_subs_off_5                              7690 non-null   float64        
 163 match_points_played_5                        8254 non-null   float64        
 164 match_points_notplayed_5                     6216 non-null   float64        
 165 total_goals_team_5                           9238 non-null   float64        
 166 total_goals_team_played_5                    6996 non-null   float64        
 167 total_goals_team_conceded_5                  9238 non-null   float64        
 168 total_goals_team_conceded_played_5           6996 non-null   float64        
 169 clean_sheet_flg_played_5                     8254 non-null   float64        
 170 clean_sheet_flg_notplayed_5                  6216 non-null   float64        
 171 lineup_rate_5                                8254 non-null   float64        
 172 minutes_per_game_5                           8254 non-null   float64        
 173 goals_per_Game_5                             8254 non-null   float64        
 174 assists_per_game_5                           8254 non-null   float64        
 175 own_goals_per_game_5                         8254 non-null   float64        
 176 yellow_cards_per_game_5                      8254 non-null   float64        
 177 second_yellow_card_per_game_5                8254 non-null   float64        
 178 red_card_per_game_5                          8254 non-null   float64        
 179 team_goals_per_game_5                        6996 non-null   float64        
 180 points_per_game_5                            8254 non-null   float64        
 181 team_conceeded_goals_per_game_5              6996 non-null   float64        
 182 clean_sheet_per_game_5                       8254 non-null   float64        
 183 team_goals_per_game_not_played_5             3876 non-null   float64        
 184 clean_sheet_per_game_not_played_5            6216 non-null   float64        
 185 team_conceeded_goals_per_game_not_played_5   3876 non-null   float64        
 186 points_per_game_not_played_5                 6216 non-null   float64        
 187 minutes_played_coverage_played_5             8254 non-null   float64        
 188 minutes_played_coverage_all_5                9381 non-null   float64        
 189 points_played_coverage_5                     8254 non-null   float64        
 190 points_not_played_coverage_5                 6216 non-null   float64        
 191 Injury_5                                     655 non-null    float64        
 192 Suspension_5                                 563 non-null    float64        
 193 not in squad_5                               3719 non-null   float64        
 194 on the bench _5                              2456 non-null   float64        
 195 injury_rate_5                                655 non-null    float64        
 196 suspension_rate_5                            563 non-null    float64        
 197 on_the_bench_rate_5                          2456 non-null   float64        
 198 not_in_squad_rate_5                          3719 non-null   float64        
 199 last_played_game_recency_5                   9381 non-null   timedelta64[ns]
dtypes: float64(168), int32(24), int64(4), timedelta64[ns](4)
memory usage: 13.5+ MB

Stats in National Matches

A football player can also play for his national team. National team stats can also be helpful to predict transfer fee. Here the difficult part of this dataset is to get the matches of players, since they can play multiple under levels also like Under 21, Under 19 etc. Here is the link of national matches. I first scraped the clubs in "national_urls_scraper.ipynb" then I looped for different national level clubs and for all players to create dataset.

The remaining part of national stats matches and features are just like club matches.

The dataset pattern is like club matches dateset:

national_stats = pd.read_pickle('C:/Users/YAVUZ/Transfer Fee Project/1.Feature Engineering/National_Stats_Features_All.pkl')
national_stats.info()

<class 'pandas.core.frame.DataFrame'>
Index: 6534 entries, 3104833 to 1115385
Data columns (total 200 columns):
 #   Column                                                Non-Null Count  Dtype          
---  ------                                                --------------  -----          
 0   match_date_National_30                                6534 non-null   int64          
 1   starting_lineup_National_30                           6534 non-null   int32          
 2   matches_played_flag_National_30                       6534 non-null   int32          
 3   goals_National_30                                     6534 non-null   float64        
 4   assists_National_30                                   6534 non-null   float64        
 5   own_goals_National_30                                 6534 non-null   float64        
 6   yellow_card_flag_National_30                          6534 non-null   int32          
 7   second_yellow_card_flag_National_30                   6534 non-null   int32          
 8   red_card_flag_National_30                             6534 non-null   int32          
 9   minutes_played_National_30                            6534 non-null   float64        
 10  substitution_off_flag_National_30                     6534 non-null   int32          
 11  match_played_rate_National_30                         6534 non-null   float64        
 12  rate_subs_off_National_30                             5843 non-null   float64        
 13  match_points_played_National_30                       6272 non-null   float64        
 14  match_points_notplayed_National_30                    5946 non-null   float64        
 15  total_goals_team_National_30                          6057 non-null   float64        
 16  total_goals_team_played_National_30                   5375 non-null   float64        
 17  total_goals_team_conceded_National_30                 6057 non-null   float64        
 18  total_goals_team_conceded_played_National_30          5375 non-null   float64        
 19  clean_sheet_flg_played_National_30                    6272 non-null   float64        
 20  clean_sheet_flg_notplayed_National_30                 5946 non-null   float64        
 21  lineup_rate_National_30                               6272 non-null   float64        
 22  minutes_per_game_National_30                          6272 non-null   float64        
 23  goals_per_Game_National_30                            6272 non-null   float64        
 24  assists_per_game_National_30                          6272 non-null   float64        
 25  own_goals_per_game_National_30                        6272 non-null   float64        
 26  yellow_cards_per_game_National_30                     6272 non-null   float64        
 27  second_yellow_card_per_game_National_30               6272 non-null   float64        
 28  red_card_per_game_National_30                         6272 non-null   float64        
 29  team_goals_per_game_National_30                       5375 non-null   float64        
 30  points_per_game_National_30                           6272 non-null   float64        
 31  team_conceeded_goals_per_game_National_30             5375 non-null   float64        
 32  clean_sheet_per_game_National_30                      6272 non-null   float64        
 33  team_goals_per_game_not_played_National_30            5065 non-null   float64        
 34  clean_sheet_per_game_not_played_National_30           5946 non-null   float64        
 35  team_conceeded_goals_per_game_not_played_National_30  5065 non-null   float64        
 36  points_per_game_not_played_National_30                5946 non-null   float64        
 37  minutes_played_coverage_played_National_30            6272 non-null   float64        
 38  minutes_played_coverage_all_National_30               6534 non-null   float64        
 39  points_played_coverage_National_30                    6272 non-null   float64        
 40  points_not_played_coverage_National_30                5946 non-null   float64        
 41  Injury_National_30                                    1352 non-null   float64        
 42  Suspension_National_30                                203 non-null    float64        
 43  not in squad_National_30                              4852 non-null   float64        
 44  on the bench_National_30                              5033 non-null   float64        
 45  injury_rate_National_30                               1352 non-null   float64        
 46  suspension_rate_National_30                           203 non-null    float64        
 47  on_the_bench_rate_National_30                         5033 non-null   float64        
 48  not_in_squad_rate_National_30                         4852 non-null   float64        
 49  last_played_game_recency_National_30                  6534 non-null   timedelta64[ns]
 50  match_date_National_20                                6534 non-null   int64          
 51  starting_lineup_National_20                           6534 non-null   int32          
 52  matches_played_flag_National_20                       6534 non-null   int32          
 53  goals_National_20                                     6534 non-null   float64        
 54  assists_National_20                                   6534 non-null   float64        
 55  own_goals_National_20                                 6534 non-null   float64        
 56  yellow_card_flag_National_20                          6534 non-null   int32          
 57  second_yellow_card_flag_National_20                   6534 non-null   int32          
 58  red_card_flag_National_20                             6534 non-null   int32          
 59  minutes_played_National_20                            6534 non-null   float64        
 60  substitution_off_flag_National_20                     6534 non-null   int32          
 61  match_played_rate_National_20                         6534 non-null   float64        
 62  rate_subs_off_National_20                             5720 non-null   float64        
 63  match_points_played_National_20                       6187 non-null   float64        
 64  match_points_notplayed_National_20                    5918 non-null   float64        
 65  total_goals_team_National_20                          6055 non-null   float64        
 66  total_goals_team_played_National_20                   5190 non-null   float64        
 67  total_goals_team_conceded_National_20                 6055 non-null   float64        
 68  total_goals_team_conceded_played_National_20          5190 non-null   float64        
 69  clean_sheet_flg_played_National_20                    6187 non-null   float64        
 70  clean_sheet_flg_notplayed_National_20                 5918 non-null   float64        
 71  lineup_rate_National_20                               6187 non-null   float64        
 72  minutes_per_game_National_20                          6187 non-null   float64        
 73  goals_per_Game_National_20                            6187 non-null   float64        
 74  assists_per_game_National_20                          6187 non-null   float64        
 75  own_goals_per_game_National_20                        6187 non-null   float64        
 76  yellow_cards_per_game_National_20                     6187 non-null   float64        
 77  second_yellow_card_per_game_National_20               6187 non-null   float64        
 78  red_card_per_game_National_20                         6187 non-null   float64        
 79  team_goals_per_game_National_20                       5190 non-null   float64        
 80  points_per_game_National_20                           6187 non-null   float64        
 81  team_conceeded_goals_per_game_National_20             5190 non-null   float64        
 82  clean_sheet_per_game_National_20                      6187 non-null   float64        
 83  team_goals_per_game_not_played_National_20            4852 non-null   float64        
 84  clean_sheet_per_game_not_played_National_20           5918 non-null   float64        
 85  team_conceeded_goals_per_game_not_played_National_20  4852 non-null   float64        
 86  points_per_game_not_played_National_20                5918 non-null   float64        
 87  minutes_played_coverage_played_National_20            6187 non-null   float64        
 88  minutes_played_coverage_all_National_20               6534 non-null   float64        
 89  points_played_coverage_National_20                    6187 non-null   float64        
 90  points_not_played_coverage_National_20                5918 non-null   float64        
 91  Injury_National_20                                    1163 non-null   float64        
 92  Suspension_National_20                                168 non-null    float64        
 93  not in squad_National_20                              4643 non-null   float64        
 94  on the bench_National_20                              4718 non-null   float64        
 95  injury_rate_National_20                               1163 non-null   float64        
 96  suspension_rate_National_20                           168 non-null    float64        
 97  on_the_bench_rate_National_20                         4718 non-null   float64        
 98  not_in_squad_rate_National_20                         4643 non-null   float64        
 99  last_played_game_recency_National_20                  6534 non-null   timedelta64[ns]
 100 match_date_National_10                                6534 non-null   int64          
 101 starting_lineup_National_10                           6534 non-null   int32          
 102 matches_played_flag_National_10                       6534 non-null   int32          
 103 goals_National_10                                     6534 non-null   float64        
 104 assists_National_10                                   6534 non-null   float64        
 105 own_goals_National_10                                 6534 non-null   float64        
 106 yellow_card_flag_National_10                          6534 non-null   int32          
 107 second_yellow_card_flag_National_10                   6534 non-null   int32          
 108 red_card_flag_National_10                             6534 non-null   int32          
 109 minutes_played_National_10                            6534 non-null   float64        
 110 substitution_off_flag_National_10                     6534 non-null   int32          
 111 match_played_rate_National_10                         6534 non-null   float64        
 112 rate_subs_off_National_10                             5335 non-null   float64        
 113 match_points_played_National_10                       5964 non-null   float64        
 114 match_points_notplayed_National_10                    5706 non-null   float64        
 115 total_goals_team_National_10                          6033 non-null   float64        
 116 total_goals_team_played_National_10                   4556 non-null   float64        
 117 total_goals_team_conceded_National_10                 6033 non-null   float64        
 118 total_goals_team_conceded_played_National_10          4556 non-null   float64        
 119 clean_sheet_flg_played_National_10                    5964 non-null   float64        
 120 clean_sheet_flg_notplayed_National_10                 5706 non-null   float64        
 121 lineup_rate_National_10                               5964 non-null   float64        
 122 minutes_per_game_National_10                          5964 non-null   float64        
 123 goals_per_Game_National_10                            5964 non-null   float64        
 124 assists_per_game_National_10                          5964 non-null   float64        
 125 own_goals_per_game_National_10                        5964 non-null   float64        
 126 yellow_cards_per_game_National_10                     5964 non-null   float64        
 127 second_yellow_card_per_game_National_10               5964 non-null   float64        
 128 red_card_per_game_National_10                         5964 non-null   float64        
 129 team_goals_per_game_National_10                       4556 non-null   float64        
 130 points_per_game_National_10                           5964 non-null   float64        
 131 team_conceeded_goals_per_game_National_10             4556 non-null   float64        
 132 clean_sheet_per_game_National_10                      5964 non-null   float64        
 133 team_goals_per_game_not_played_National_10            4007 non-null   float64        
 134 clean_sheet_per_game_not_played_National_10           5706 non-null   float64        
 135 team_conceeded_goals_per_game_not_played_National_10  4007 non-null   float64        
 136 points_per_game_not_played_National_10                5706 non-null   float64        
 137 minutes_played_coverage_played_National_10            5964 non-null   float64        
 138 minutes_played_coverage_all_National_10               6534 non-null   float64        
 139 points_played_coverage_National_10                    5964 non-null   float64        
 140 points_not_played_coverage_National_10                5706 non-null   float64        
 141 Injury_National_10                                    724 non-null    float64        
 142 Suspension_National_10                                109 non-null    float64        
 143 not in squad_National_10                              3919 non-null   float64        
 144 on the bench_National_10                              4031 non-null   float64        
 145 injury_rate_National_10                               724 non-null    float64        
 146 suspension_rate_National_10                           109 non-null    float64        
 147 on_the_bench_rate_National_10                         4031 non-null   float64        
 148 not_in_squad_rate_National_10                         3919 non-null   float64        
 149 last_played_game_recency_National_10                  6534 non-null   timedelta64[ns]
 150 match_date_National_5                                 6534 non-null   int64          
 151 starting_lineup_National_5                            6534 non-null   int32          
 152 matches_played_flag_National_5                        6534 non-null   int32          
 153 goals_National_5                                      6534 non-null   float64        
 154 assists_National_5                                    6534 non-null   float64        
 155 own_goals_National_5                                  6534 non-null   float64        
 156 yellow_card_flag_National_5                           6534 non-null   int32          
 157 second_yellow_card_flag_National_5                    6534 non-null   int32          
 158 red_card_flag_National_5                              6534 non-null   int32          
 159 minutes_played_National_5                             6534 non-null   float64        
 160 substitution_off_flag_National_5                      6534 non-null   int32          
 161 match_played_rate_National_5                          6534 non-null   float64        
 162 rate_subs_off_National_5                              4691 non-null   float64        
 163 match_points_played_National_5                        5572 non-null   float64        
 164 match_points_notplayed_National_5                     5079 non-null   float64        
 165 total_goals_team_National_5                           5803 non-null   float64        
 166 total_goals_team_played_National_5                    3500 non-null   float64        
 167 total_goals_team_conceded_National_5                  5803 non-null   float64        
 168 total_goals_team_conceded_played_National_5           3500 non-null   float64        
 169 clean_sheet_flg_played_National_5                     5572 non-null   float64        
 170 clean_sheet_flg_notplayed_National_5                  5079 non-null   float64        
 171 lineup_rate_National_5                                5572 non-null   float64        
 172 minutes_per_game_National_5                           5572 non-null   float64        
 173 goals_per_Game_National_5                             5572 non-null   float64        
 174 assists_per_game_National_5                           5572 non-null   float64        
 175 own_goals_per_game_National_5                         5572 non-null   float64        
 176 yellow_cards_per_game_National_5                      5572 non-null   float64        
 177 second_yellow_card_per_game_National_5                5572 non-null   float64        
 178 red_card_per_game_National_5                          5572 non-null   float64        
 179 team_goals_per_game_National_5                        3500 non-null   float64        
 180 points_per_game_National_5                            5572 non-null   float64        
 181 team_conceeded_goals_per_game_National_5              3500 non-null   float64        
 182 clean_sheet_per_game_National_5                       5572 non-null   float64        
 183 team_goals_per_game_not_played_National_5             2373 non-null   float64        
 184 clean_sheet_per_game_not_played_National_5            5079 non-null   float64        
 185 team_conceeded_goals_per_game_not_played_National_5   2373 non-null   float64        
 186 points_per_game_not_played_National_5                 5079 non-null   float64        
 187 minutes_played_coverage_played_National_5             5572 non-null   float64        
 188 minutes_played_coverage_all_National_5                6534 non-null   float64        
 189 points_played_coverage_National_5                     5572 non-null   float64        
 190 points_not_played_coverage_National_5                 5079 non-null   float64        
 191 Injury_National_5                                     390 non-null    float64        
 192 Suspension_National_5                                 62 non-null     float64        
 193 not in squad_National_5                               2839 non-null   float64        
 194 on the bench_National_5                               3191 non-null   float64        
 195 injury_rate_National_5                                390 non-null    float64        
 196 suspension_rate_National_5                            62 non-null     float64        
 197 on_the_bench_rate_National_5                          3191 non-null   float64        
 198 not_in_squad_rate_National_5                          2839 non-null   float64        
 199 last_played_game_recency_National_5                   6534 non-null   timedelta64[ns]
dtypes: float64(168), int32(24), int64(4), timedelta64[ns](4)
memory usage: 9.4+ MB

Achievements

Finally, achievements are also very important for predicting transfer fee. The fee can increase if the player wins top goal scorer awards, or cups. I decided to scrape achievements from the link

In Feature engineering folder I created number of achievements and number of distinct achievements of a player as features to be used in the prediction model.

The data pattern for achievement dataset is:

achievements = pd.read_pickle('C:/Users/YAVUZ/Transfer Fee Project/1.Feature Engineering/achievement_features.pkl')
achievements.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4199 entries, 0 to 4198
Data columns (total 3 columns):
 #   Column                 Non-Null Count  Dtype 
---  ------                 --------------  ----- 
 0   Transfer_id            4199 non-null   object
 1   Total_Achievements     4199 non-null   int64 
 2   Distinct_Achievements  4199 non-null   int64 
dtypes: int64(2), object(1)
memory usage: 98.5+ KB

#Merge datasets
df = transfer_detail.merge(profile, on=['Transfer_id'], how='left')
df=df.merge(achievements, on=['Transfer_id'], how='left')
df=df.merge(national_stats, on=['Transfer_id'], how='left')
df=df.merge(stats, on=['Transfer_id'], how='left')

#import libraries
import pandas as pd
import math
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.model_selection import train_test_split
from lightgbm import LGBMRegressor
from sklearn.metrics import mean_absolute_error,mean_squared_error,r2_score
from math import sqrt
from sklearn.model_selection import GridSearchCV
import plotly.express as px
from datetime import timedelta, date
import datetime

import tensorflow as tf

from tensorflow import keras
from tensorflow.keras import layers
from tensorflow.keras.layers.experimental import preprocessing
pd.set_option('display.float_format', lambda x: '%.3f' % x)

Data Exploration

Let's explore the dataset a little bit.First i will take head,tail and describe for the dataframe. Then, I will ask 4 questions to the data and get the answers of each by visualizing.

• How many players are in the data in each year? (2016-2020)
• What is the average fee in each year?
• How many players exist in each position?
• What is the average fee in each positions?

df.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 9499 entries, 0 to 9498
Data columns (total 440 columns):
 #   Column                                                Non-Null Count  Dtype          
---  ------                                                --------------  -----          
 0   Transfer_Link_x                                       9499 non-null   object         
 1   Transfer_id                                           9499 non-null   object         
 2   id_x                                                  9499 non-null   object         
 3   NOF_Transfers                                         9499 non-null   object         
 4   Avg_Market_Value                                      7729 non-null   object         
 5   Tot_Fee_Loan_Fee_Exc                                  9499 non-null   object         
 6   Avg_Fee                                               4166 non-null   object         
 7   Tot_Fee_Loan_Fee_Inc                                  9499 non-null   object         
 8   Age_at_Time_of_transfer                               9499 non-null   object         
 9   Contract_Left_at_Time_of_transfer                     7496 non-null   object         
 10  Market_Value_at_Time_of_transfer                      9499 non-null   object         
 11  Team_Left_Tier                                        9447 non-null   object         
 12  Team_Joined_Tier                                      9447 non-null   object         
 13  Team_Left_League                                      9447 non-null   object         
 14  Team_Joined_League                                    9447 non-null   object         
 15  Fee                                                   9499 non-null   object         
 16  Transfer_Season                                       9499 non-null   object         
 17  Transfer_Date_x                                       9499 non-null   object         
 18  Team_Left                                             9499 non-null   object         
 19  Team_Joined                                           9499 non-null   object         
 20  Country_Left                                          9141 non-null   object         
 21  Country_Joined                                        9371 non-null   object         
 22  Country_Change_Flag                                   9499 non-null   object         
 23  League_Change_Flag                                    9499 non-null   object         
 24  League_Tier_Up_Flag                                   9499 non-null   object         
 25  League_Tier_Down_Flag                                 9499 non-null   object         
 26  Transfer_Link_y                                       9499 non-null   object         
 27  id_y                                                  9499 non-null   object         
 28  Transfer_Date_y                                       9499 non-null   object         
 29  Date_of_birth                                         9499 non-null   object         
 30  Place_of_birth                                        9499 non-null   object         
 31  Height                                                9499 non-null   object         
 32  Citizenship                                           9499 non-null   object         
 33  Position                                              9499 non-null   object         
 34  Foot                                                  9499 non-null   object         
 35  Main_position                                         9499 non-null   object         
 36  other_position1                                       9499 non-null   object         
 37  other_position2                                       9499 non-null   object         
 38  Total_Achievements                                    4199 non-null   float64        
 39  Distinct_Achievements                                 4199 non-null   float64        
 40  match_date_National_30                                6534 non-null   float64        
 41  starting_lineup_National_30                           6534 non-null   float64        
 42  matches_played_flag_National_30                       6534 non-null   float64        
 43  goals_National_30                                     6534 non-null   float64        
 44  assists_National_30                                   6534 non-null   float64        
 45  own_goals_National_30                                 6534 non-null   float64        
 46  yellow_card_flag_National_30                          6534 non-null   float64        
 47  second_yellow_card_flag_National_30                   6534 non-null   float64        
 48  red_card_flag_National_30                             6534 non-null   float64        
 49  minutes_played_National_30                            6534 non-null   float64        
 50  substitution_off_flag_National_30                     6534 non-null   float64        
 51  match_played_rate_National_30                         6534 non-null   float64        
 52  rate_subs_off_National_30                             5843 non-null   float64        
 53  match_points_played_National_30                       6272 non-null   float64        
 54  match_points_notplayed_National_30                    5946 non-null   float64        
 55  total_goals_team_National_30                          6057 non-null   float64        
 56  total_goals_team_played_National_30                   5375 non-null   float64        
 57  total_goals_team_conceded_National_30                 6057 non-null   float64        
 58  total_goals_team_conceded_played_National_30          5375 non-null   float64        
 59  clean_sheet_flg_played_National_30                    6272 non-null   float64        
 60  clean_sheet_flg_notplayed_National_30                 5946 non-null   float64        
 61  lineup_rate_National_30                               6272 non-null   float64        
 62  minutes_per_game_National_30                          6272 non-null   float64        
 63  goals_per_Game_National_30                            6272 non-null   float64        
 64  assists_per_game_National_30                          6272 non-null   float64        
 65  own_goals_per_game_National_30                        6272 non-null   float64        
 66  yellow_cards_per_game_National_30                     6272 non-null   float64        
 67  second_yellow_card_per_game_National_30               6272 non-null   float64        
 68  red_card_per_game_National_30                         6272 non-null   float64        
 69  team_goals_per_game_National_30                       5375 non-null   float64        
 70  points_per_game_National_30                           6272 non-null   float64        
 71  team_conceeded_goals_per_game_National_30             5375 non-null   float64        
 72  clean_sheet_per_game_National_30                      6272 non-null   float64        
 73  team_goals_per_game_not_played_National_30            5065 non-null   float64        
 74  clean_sheet_per_game_not_played_National_30           5946 non-null   float64        
 75  team_conceeded_goals_per_game_not_played_National_30  5065 non-null   float64        
 76  points_per_game_not_played_National_30                5946 non-null   float64        
 77  minutes_played_coverage_played_National_30            6272 non-null   float64        
 78  minutes_played_coverage_all_National_30               6534 non-null   float64        
 79  points_played_coverage_National_30                    6272 non-null   float64        
 80  points_not_played_coverage_National_30                5946 non-null   float64        
 81  Injury_National_30                                    1352 non-null   float64        
 82  Suspension_National_30                                203 non-null    float64        
 83  not in squad_National_30                              4852 non-null   float64        
 84  on the bench_National_30                              5033 non-null   float64        
 85  injury_rate_National_30                               1352 non-null   float64        
 86  suspension_rate_National_30                           203 non-null    float64        
 87  on_the_bench_rate_National_30                         5033 non-null   float64        
 88  not_in_squad_rate_National_30                         4852 non-null   float64        
 89  last_played_game_recency_National_30                  6534 non-null   timedelta64[ns]
 90  match_date_National_20                                6534 non-null   float64        
 91  starting_lineup_National_20                           6534 non-null   float64        
 92  matches_played_flag_National_20                       6534 non-null   float64        
 93  goals_National_20                                     6534 non-null   float64        
 94  assists_National_20                                   6534 non-null   float64        
 95  own_goals_National_20                                 6534 non-null   float64        
 96  yellow_card_flag_National_20                          6534 non-null   float64        
 97  second_yellow_card_flag_National_20                   6534 non-null   float64        
 98  red_card_flag_National_20                             6534 non-null   float64        
 99  minutes_played_National_20                            6534 non-null   float64        
 100 substitution_off_flag_National_20                     6534 non-null   float64        
 101 match_played_rate_National_20                         6534 non-null   float64        
 102 rate_subs_off_National_20                             5720 non-null   float64        
 103 match_points_played_National_20                       6187 non-null   float64        
 104 match_points_notplayed_National_20                    5918 non-null   float64        
 105 total_goals_team_National_20                          6055 non-null   float64        
 106 total_goals_team_played_National_20                   5190 non-null   float64        
 107 total_goals_team_conceded_National_20                 6055 non-null   float64        
 108 total_goals_team_conceded_played_National_20          5190 non-null   float64        
 109 clean_sheet_flg_played_National_20                    6187 non-null   float64        
 110 clean_sheet_flg_notplayed_National_20                 5918 non-null   float64        
 111 lineup_rate_National_20                               6187 non-null   float64        
 112 minutes_per_game_National_20                          6187 non-null   float64        
 113 goals_per_Game_National_20                            6187 non-null   float64        
 114 assists_per_game_National_20                          6187 non-null   float64        
 115 own_goals_per_game_National_20                        6187 non-null   float64        
 116 yellow_cards_per_game_National_20                     6187 non-null   float64        
 117 second_yellow_card_per_game_National_20               6187 non-null   float64        
 118 red_card_per_game_National_20                         6187 non-null   float64        
 119 team_goals_per_game_National_20                       5190 non-null   float64        
 120 points_per_game_National_20                           6187 non-null   float64        
 121 team_conceeded_goals_per_game_National_20             5190 non-null   float64        
 122 clean_sheet_per_game_National_20                      6187 non-null   float64        
 123 team_goals_per_game_not_played_National_20            4852 non-null   float64        
 124 clean_sheet_per_game_not_played_National_20           5918 non-null   float64        
 125 team_conceeded_goals_per_game_not_played_National_20  4852 non-null   float64        
 126 points_per_game_not_played_National_20                5918 non-null   float64        
 127 minutes_played_coverage_played_National_20            6187 non-null   float64        
 128 minutes_played_coverage_all_National_20               6534 non-null   float64        
 129 points_played_coverage_National_20                    6187 non-null   float64        
 130 points_not_played_coverage_National_20                5918 non-null   float64        
 131 Injury_National_20                                    1163 non-null   float64        
 132 Suspension_National_20                                168 non-null    float64        
 133 not in squad_National_20                              4643 non-null   float64        
 134 on the bench_National_20                              4718 non-null   float64        
 135 injury_rate_National_20                               1163 non-null   float64        
 136 suspension_rate_National_20                           168 non-null    float64        
 137 on_the_bench_rate_National_20                         4718 non-null   float64        
 138 not_in_squad_rate_National_20                         4643 non-null   float64        
 139 last_played_game_recency_National_20                  6534 non-null   timedelta64[ns]
 140 match_date_National_10                                6534 non-null   float64        
 141 starting_lineup_National_10                           6534 non-null   float64        
 142 matches_played_flag_National_10                       6534 non-null   float64        
 143 goals_National_10                                     6534 non-null   float64        
 144 assists_National_10                                   6534 non-null   float64        
 145 own_goals_National_10                                 6534 non-null   float64        
 146 yellow_card_flag_National_10                          6534 non-null   float64        
 147 second_yellow_card_flag_National_10                   6534 non-null   float64        
 148 red_card_flag_National_10                             6534 non-null   float64        
 149 minutes_played_National_10                            6534 non-null   float64        
 150 substitution_off_flag_National_10                     6534 non-null   float64        
 151 match_played_rate_National_10                         6534 non-null   float64        
 152 rate_subs_off_National_10                             5335 non-null   float64        
 153 match_points_played_National_10                       5964 non-null   float64        
 154 match_points_notplayed_National_10                    5706 non-null   float64        
 155 total_goals_team_National_10                          6033 non-null   float64        
 156 total_goals_team_played_National_10                   4556 non-null   float64        
 157 total_goals_team_conceded_National_10                 6033 non-null   float64        
 158 total_goals_team_conceded_played_National_10          4556 non-null   float64        
 159 clean_sheet_flg_played_National_10                    5964 non-null   float64        
 160 clean_sheet_flg_notplayed_National_10                 5706 non-null   float64        
 161 lineup_rate_National_10                               5964 non-null   float64        
 162 minutes_per_game_National_10                          5964 non-null   float64        
 163 goals_per_Game_National_10                            5964 non-null   float64        
 164 assists_per_game_National_10                          5964 non-null   float64        
 165 own_goals_per_game_National_10                        5964 non-null   float64        
 166 yellow_cards_per_game_National_10                     5964 non-null   float64        
 167 second_yellow_card_per_game_National_10               5964 non-null   float64        
 168 red_card_per_game_National_10                         5964 non-null   float64        
 169 team_goals_per_game_National_10                       4556 non-null   float64        
 170 points_per_game_National_10                           5964 non-null   float64        
 171 team_conceeded_goals_per_game_National_10             4556 non-null   float64        
 172 clean_sheet_per_game_National_10                      5964 non-null   float64        
 173 team_goals_per_game_not_played_National_10            4007 non-null   float64        
 174 clean_sheet_per_game_not_played_National_10           5706 non-null   float64        
 175 team_conceeded_goals_per_game_not_played_National_10  4007 non-null   float64        
 176 points_per_game_not_played_National_10                5706 non-null   float64        
 177 minutes_played_coverage_played_National_10            5964 non-null   float64        
 178 minutes_played_coverage_all_National_10               6534 non-null   float64        
 179 points_played_coverage_National_10                    5964 non-null   float64        
 180 points_not_played_coverage_National_10                5706 non-null   float64        
 181 Injury_National_10                                    724 non-null    float64        
 182 Suspension_National_10                                109 non-null    float64        
 183 not in squad_National_10                              3919 non-null   float64        
 184 on the bench_National_10                              4031 non-null   float64        
 185 injury_rate_National_10                               724 non-null    float64        
 186 suspension_rate_National_10                           109 non-null    float64        
 187 on_the_bench_rate_National_10                         4031 non-null   float64        
 188 not_in_squad_rate_National_10                         3919 non-null   float64        
 189 last_played_game_recency_National_10                  6534 non-null   timedelta64[ns]
 190 match_date_National_5                                 6534 non-null   float64        
 191 starting_lineup_National_5                            6534 non-null   float64        
 192 matches_played_flag_National_5                        6534 non-null   float64        
 193 goals_National_5                                      6534 non-null   float64        
 194 assists_National_5                                    6534 non-null   float64        
 195 own_goals_National_5                                  6534 non-null   float64        
 196 yellow_card_flag_National_5                           6534 non-null   float64        
 197 second_yellow_card_flag_National_5                    6534 non-null   float64        
 198 red_card_flag_National_5                              6534 non-null   float64        
 199 minutes_played_National_5                             6534 non-null   float64        
 200 substitution_off_flag_National_5                      6534 non-null   float64        
 201 match_played_rate_National_5                          6534 non-null   float64        
 202 rate_subs_off_National_5                              4691 non-null   float64        
 203 match_points_played_National_5                        5572 non-null   float64        
 204 match_points_notplayed_National_5                     5079 non-null   float64        
 205 total_goals_team_National_5                           5803 non-null   float64        
 206 total_goals_team_played_National_5                    3500 non-null   float64        
 207 total_goals_team_conceded_National_5                  5803 non-null   float64        
 208 total_goals_team_conceded_played_National_5           3500 non-null   float64        
 209 clean_sheet_flg_played_National_5                     5572 non-null   float64        
 210 clean_sheet_flg_notplayed_National_5                  5079 non-null   float64        
 211 lineup_rate_National_5                                5572 non-null   float64        
 212 minutes_per_game_National_5                           5572 non-null   float64        
 213 goals_per_Game_National_5                             5572 non-null   float64        
 214 assists_per_game_National_5                           5572 non-null   float64        
 215 own_goals_per_game_National_5                         5572 non-null   float64        
 216 yellow_cards_per_game_National_5                      5572 non-null   float64        
 217 second_yellow_card_per_game_National_5                5572 non-null   float64        
 218 red_card_per_game_National_5                          5572 non-null   float64        
 219 team_goals_per_game_National_5                        3500 non-null   float64        
 220 points_per_game_National_5                            5572 non-null   float64        
 221 team_conceeded_goals_per_game_National_5              3500 non-null   float64        
 222 clean_sheet_per_game_National_5                       5572 non-null   float64        
 223 team_goals_per_game_not_played_National_5             2373 non-null   float64        
 224 clean_sheet_per_game_not_played_National_5            5079 non-null   float64        
 225 team_conceeded_goals_per_game_not_played_National_5   2373 non-null   float64        
 226 points_per_game_not_played_National_5                 5079 non-null   float64        
 227 minutes_played_coverage_played_National_5             5572 non-null   float64        
 228 minutes_played_coverage_all_National_5                6534 non-null   float64        
 229 points_played_coverage_National_5                     5572 non-null   float64        
 230 points_not_played_coverage_National_5                 5079 non-null   float64        
 231 Injury_National_5                                     390 non-null    float64        
 232 Suspension_National_5                                 62 non-null     float64        
 233 not in squad_National_5                               2839 non-null   float64        
 234 on the bench_National_5                               3191 non-null   float64        
 235 injury_rate_National_5                                390 non-null    float64        
 236 suspension_rate_National_5                            62 non-null     float64        
 237 on_the_bench_rate_National_5                          3191 non-null   float64        
 238 not_in_squad_rate_National_5                          2839 non-null   float64        
 239 last_played_game_recency_National_5                   6534 non-null   timedelta64[ns]
 240 Date_30                                               9381 non-null   float64        
 241 starting_lineup_30                                    9381 non-null   float64        
 242 matches_played_flag_30                                9381 non-null   float64        
 243 Goals_30                                              9381 non-null   float64        
 244 Assists_30                                            9381 non-null   float64        
 245 Own goals_30                                          9381 non-null   float64        
 246 yellow_card_flag_30                                   9381 non-null   float64        
 247 second_yellow_card_flag_30                            9381 non-null   float64        
 248 red_card_flag_30                                      9381 non-null   float64        
 249 Minutes played_30                                     9381 non-null   float64        
 250 substitution_off_flag_30                              9381 non-null   float64        
 251 match_played_rate_30                                  9381 non-null   float64        
 252 rate_subs_off_30                                      9208 non-null   float64        
 253 match_points_played_30                                9282 non-null   float64        
 254 match_points_notplayed_30                             9098 non-null   float64        
 255 total_goals_team_30                                   9287 non-null   float64        
 256 total_goals_team_played_30                            9002 non-null   float64        
 257 total_goals_team_conceded_30                          9287 non-null   float64        
 258 total_goals_team_conceded_played_30                   9002 non-null   float64        
 259 clean_sheet_flg_played_30                             9282 non-null   float64        
 260 clean_sheet_flg_notplayed_30                          9098 non-null   float64        
 261 lineup_rate_30                                        9282 non-null   float64        
 262 minutes_per_game_30                                   9282 non-null   float64        
 263 goals_per_Game_30                                     9282 non-null   float64        
 264 assists_per_game_30                                   9282 non-null   float64        
 265 own_goals_per_game_30                                 9282 non-null   float64        
 266 yellow_cards_per_game_30                              9282 non-null   float64        
 267 second_yellow_card_per_game_30                        9282 non-null   float64        
 268 red_card_per_game_30                                  9282 non-null   float64        
 269 team_goals_per_game_30                                9002 non-null   float64        
 270 points_per_game_30                                    9282 non-null   float64        
 271 team_conceeded_goals_per_game_30                      9002 non-null   float64        
 272 clean_sheet_per_game_30                               9282 non-null   float64        
 273 team_goals_per_game_not_played_30                     8724 non-null   float64        
 274 clean_sheet_per_game_not_played_30                    9098 non-null   float64        
 275 team_conceeded_goals_per_game_not_played_30           8724 non-null   float64        
 276 points_per_game_not_played_30                         9098 non-null   float64        
 277 minutes_played_coverage_played_30                     9282 non-null   float64        
 278 minutes_played_coverage_all_30                        9381 non-null   float64        
 279 points_played_coverage_30                             9282 non-null   float64        
 280 points_not_played_coverage_30                         9098 non-null   float64        
 281 Injury_30                                             2108 non-null   float64        
 282 Suspension_30                                         2218 non-null   float64        
 283 not in squad_30                                       7288 non-null   float64        
 284 on the bench _30                                      6088 non-null   float64        
 285 injury_rate_30                                        2108 non-null   float64        
 286 suspension_rate_30                                    2218 non-null   float64        
 287 on_the_bench_rate_30                                  6088 non-null   float64        
 288 not_in_squad_rate_30                                  7288 non-null   float64        
 289 last_played_game_recency_30                           9381 non-null   timedelta64[ns]
 290 Date_20                                               9381 non-null   float64        
 291 starting_lineup_20                                    9381 non-null   float64        
 292 matches_played_flag_20                                9381 non-null   float64        
 293 Goals_20                                              9381 non-null   float64        
 294 Assists_20                                            9381 non-null   float64        
 295 Own goals_20                                          9381 non-null   float64        
 296 yellow_card_flag_20                                   9381 non-null   float64        
 297 second_yellow_card_flag_20                            9381 non-null   float64        
 298 red_card_flag_20                                      9381 non-null   float64        
 299 Minutes played_20                                     9381 non-null   float64        
 300 substitution_off_flag_20                              9381 non-null   float64        
 301 match_played_rate_20                                  9381 non-null   float64        
 302 rate_subs_off_20                                      9046 non-null   float64        
 303 match_points_played_20                                9180 non-null   float64        
 304 match_points_notplayed_20                             8747 non-null   float64        
 305 total_goals_team_20                                   9268 non-null   float64        
 306 total_goals_team_played_20                            8759 non-null   float64        
 307 total_goals_team_conceded_20                          9268 non-null   float64        
 308 total_goals_team_conceded_played_20                   8759 non-null   float64        
 309 clean_sheet_flg_played_20                             9180 non-null   float64        
 310 clean_sheet_flg_notplayed_20                          8747 non-null   float64        
 311 lineup_rate_20                                        9180 non-null   float64        
 312 minutes_per_game_20                                   9180 non-null   float64        
 313 goals_per_Game_20                                     9180 non-null   float64        
 314 assists_per_game_20                                   9180 non-null   float64        
 315 own_goals_per_game_20                                 9180 non-null   float64        
 316 yellow_cards_per_game_20                              9180 non-null   float64        
 317 second_yellow_card_per_game_20                        9180 non-null   float64        
 318 red_card_per_game_20                                  9180 non-null   float64        
 319 team_goals_per_game_20                                8759 non-null   float64        
 320 points_per_game_20                                    9180 non-null   float64        
 321 team_conceeded_goals_per_game_20                      8759 non-null   float64        
 322 clean_sheet_per_game_20                               9180 non-null   float64        
 323 team_goals_per_game_not_played_20                     8133 non-null   float64        
 324 clean_sheet_per_game_not_played_20                    8747 non-null   float64        
 325 team_conceeded_goals_per_game_not_played_20           8133 non-null   float64        
 326 points_per_game_not_played_20                         8747 non-null   float64        
 327 minutes_played_coverage_played_20                     9180 non-null   float64        
 328 minutes_played_coverage_all_20                        9381 non-null   float64        
 329 points_played_coverage_20                             9180 non-null   float64        
 330 points_not_played_coverage_20                         8747 non-null   float64        
 331 Injury_20                                             1652 non-null   float64        
 332 Suspension_20                                         1745 non-null   float64        
 333 not in squad_20                                       6358 non-null   float64        
 334 on the bench _20                                      4990 non-null   float64        
 335 injury_rate_20                                        1652 non-null   float64        
 336 suspension_rate_20                                    1745 non-null   float64        
 337 on_the_bench_rate_20                                  4990 non-null   float64        
 338 not_in_squad_rate_20                                  6358 non-null   float64        
 339 last_played_game_recency_20                           9381 non-null   timedelta64[ns]
 340 Date_10                                               9381 non-null   float64        
 341 starting_lineup_10                                    9381 non-null   float64        
 342 matches_played_flag_10                                9381 non-null   float64        
 343 Goals_10                                              9381 non-null   float64        
 344 Assists_10                                            9381 non-null   float64        
 345 Own goals_10                                          9381 non-null   float64        
 346 yellow_card_flag_10                                   9381 non-null   float64        
 347 second_yellow_card_flag_10                            9381 non-null   float64        
 348 red_card_flag_10                                      9381 non-null   float64        
 349 Minutes played_10                                     9381 non-null   float64        
 350 substitution_off_flag_10                              9381 non-null   float64        
 351 match_played_rate_10                                  9381 non-null   float64        
 352 rate_subs_off_10                                      8523 non-null   float64        
 353 match_points_played_10                                8868 non-null   float64        
 354 match_points_notplayed_10                             7658 non-null   float64        
 355 total_goals_team_10                                   9261 non-null   float64        
 356 total_goals_team_played_10                            8149 non-null   float64        
 357 total_goals_team_conceded_10                          9261 non-null   float64        
 358 total_goals_team_conceded_played_10                   8149 non-null   float64        
 359 clean_sheet_flg_played_10                             8868 non-null   float64        
 360 clean_sheet_flg_notplayed_10                          7658 non-null   float64        
 361 lineup_rate_10                                        8868 non-null   float64        
 362 minutes_per_game_10                                   8868 non-null   float64        
 363 goals_per_Game_10                                     8868 non-null   float64        
 364 assists_per_game_10                                   8868 non-null   float64        
 365 own_goals_per_game_10                                 8868 non-null   float64        
 366 yellow_cards_per_game_10                              8868 non-null   float64        
 367 second_yellow_card_per_game_10                        8868 non-null   float64        
 368 red_card_per_game_10                                  8868 non-null   float64        
 369 team_goals_per_game_10                                8149 non-null   float64        
 370 points_per_game_10                                    8868 non-null   float64        
 371 team_conceeded_goals_per_game_10                      8149 non-null   float64        
 372 clean_sheet_per_game_10                               8868 non-null   float64        
 373 team_goals_per_game_not_played_10                     6451 non-null   float64        
 374 clean_sheet_per_game_not_played_10                    7658 non-null   float64        
 375 team_conceeded_goals_per_game_not_played_10           6451 non-null   float64        
 376 points_per_game_not_played_10                         7658 non-null   float64        
 377 minutes_played_coverage_played_10                     8868 non-null   float64        
 378 minutes_played_coverage_all_10                        9381 non-null   float64        
 379 points_played_coverage_10                             8868 non-null   float64        
 380 points_not_played_coverage_10                         7658 non-null   float64        
 381 Injury_10                                             1042 non-null   float64        
 382 Suspension_10                                         1064 non-null   float64        
 383 not in squad_10                                       4910 non-null   float64        
 384 on the bench _10                                      3552 non-null   float64        
 385 injury_rate_10                                        1042 non-null   float64        
 386 suspension_rate_10                                    1064 non-null   float64        
 387 on_the_bench_rate_10                                  3552 non-null   float64        
 388 not_in_squad_rate_10                                  4910 non-null   float64        
 389 last_played_game_recency_10                           9381 non-null   timedelta64[ns]
 390 Date_5                                                9381 non-null   float64        
 391 starting_lineup_5                                     9381 non-null   float64        
 392 matches_played_flag_5                                 9381 non-null   float64        
 393 Goals_5                                               9381 non-null   float64        
 394 Assists_5                                             9381 non-null   float64        
 395 Own goals_5                                           9381 non-null   float64        
 396 yellow_card_flag_5                                    9381 non-null   float64        
 397 second_yellow_card_flag_5                             9381 non-null   float64        
 398 red_card_flag_5                                       9381 non-null   float64        
 399 Minutes played_5                                      9381 non-null   float64        
 400 substitution_off_flag_5                               9381 non-null   float64        
 401 match_played_rate_5                                   9381 non-null   float64        
 402 rate_subs_off_5                                       7690 non-null   float64        
 403 match_points_played_5                                 8254 non-null   float64        
 404 match_points_notplayed_5                              6216 non-null   float64        
 405 total_goals_team_5                                    9238 non-null   float64        
 406 total_goals_team_played_5                             6996 non-null   float64        
 407 total_goals_team_conceded_5                           9238 non-null   float64        
 408 total_goals_team_conceded_played_5                    6996 non-null   float64        
 409 clean_sheet_flg_played_5                              8254 non-null   float64        
 410 clean_sheet_flg_notplayed_5                           6216 non-null   float64        
 411 lineup_rate_5                                         8254 non-null   float64        
 412 minutes_per_game_5                                    8254 non-null   float64        
 413 goals_per_Game_5                                      8254 non-null   float64        
 414 assists_per_game_5                                    8254 non-null   float64        
 415 own_goals_per_game_5                                  8254 non-null   float64        
 416 yellow_cards_per_game_5                               8254 non-null   float64        
 417 second_yellow_card_per_game_5                         8254 non-null   float64        
 418 red_card_per_game_5                                   8254 non-null   float64        
 419 team_goals_per_game_5                                 6996 non-null   float64        
 420 points_per_game_5                                     8254 non-null   float64        
 421 team_conceeded_goals_per_game_5                       6996 non-null   float64        
 422 clean_sheet_per_game_5                                8254 non-null   float64        
 423 team_goals_per_game_not_played_5                      3876 non-null   float64        
 424 clean_sheet_per_game_not_played_5                     6216 non-null   float64        
 425 team_conceeded_goals_per_game_not_played_5            3876 non-null   float64        
 426 points_per_game_not_played_5                          6216 non-null   float64        
 427 minutes_played_coverage_played_5                      8254 non-null   float64        
 428 minutes_played_coverage_all_5                         9381 non-null   float64        
 429 points_played_coverage_5                              8254 non-null   float64        
 430 points_not_played_coverage_5                          6216 non-null   float64        
 431 Injury_5                                              655 non-null    float64        
 432 Suspension_5                                          563 non-null    float64        
 433 not in squad_5                                        3719 non-null   float64        
 434 on the bench _5                                       2456 non-null   float64        
 435 injury_rate_5                                         655 non-null    float64        
 436 suspension_rate_5                                     563 non-null    float64        
 437 on_the_bench_rate_5                                   2456 non-null   float64        
 438 not_in_squad_rate_5                                   3719 non-null   float64        
 439 last_played_game_recency_5                            9381 non-null   timedelta64[ns]
dtypes: float64(394), object(38), timedelta64[ns](8)
memory usage: 32.0+ MB

df.head()

	Transfer_Link_x	Transfer_id	id_x	NOF_Transfers	Avg_Market_Value	Tot_Fee_Loan_Fee_Exc	Avg_Fee	Tot_Fee_Loan_Fee_Inc	Age_at_Time_of_transfer	Contract_Left_at_Time_of_transfer	...	points_not_played_coverage_5	Injury_5	Suspension_5	not in squad_5	on the bench _5	injury_rate_5	suspension_rate_5	on_the_bench_rate_5	not_in_squad_rate_5	last_played_game_recency_5
0	/jumplist/transfers/spieler/7161/transfer_id/1...	1391587	7161	7	2137500.000	0	NaN	200000	23 years 05 months 18 days	02 Years 05 Months 29 Days (Jun 30, 2018)	...	0.670	nan	nan	nan	3.000	nan	nan	0.600	nan	27 days
1	/jumplist/transfers/spieler/147266/transfer_id...	1381390	147266	4	1283333.333	0	NaN	0	25 years 09 months 03 days	NaN	...	nan	nan	nan	nan	nan	nan	nan	nan	nan	57 days
2	/jumplist/transfers/spieler/211655/transfer_id...	1389543	211655	1	NaN	320000	320000.000	320000	26 years 04 months 12 days	01 Years 11 Months 29 Days (Dec 31, 2017)	...	nan	nan	nan	nan	nan	nan	nan	nan	nan	104 days
3	/jumplist/transfers/spieler/81820/transfer_id/...	1386344	81820	2	100000.000	2350000	1175000.000	2350000	29 years 04 months 00 days	11 Months 29 Days (Dec 31, 2016)	...	0.330	nan	nan	2.000	1.000	nan	nan	0.200	0.400	102 days
4	/jumplist/transfers/spieler/334042/transfer_id...	1381389	334042	1	NaN	0	NaN	0	19 years 09 months 08 days	NaN	...	nan	nan	nan	nan	nan	nan	nan	nan	nan	75 days

5 rows × 440 columns

df.tail()

	Transfer_Link_x	Transfer_id	id_x	NOF_Transfers	Avg_Market_Value	Tot_Fee_Loan_Fee_Exc	Avg_Fee	Tot_Fee_Loan_Fee_Inc	Age_at_Time_of_transfer	Contract_Left_at_Time_of_transfer	...	points_not_played_coverage_5	Injury_5	Suspension_5	not in squad_5	on the bench _5	injury_rate_5	suspension_rate_5	on_the_bench_rate_5	not_in_squad_rate_5	last_played_game_recency_5
9494	/jumplist/transfers/spieler/262300/transfer_id...	3104833	262300	5	250000.000	68000	68000.000	68000	24 years 04 months 02 days	NaN	...	nan	nan	nan	nan	nan	nan	nan	nan	nan	100 days
9495	/jumplist/transfers/spieler/60761/transfer_id/...	3104424	60761	4	916666.667	1200000	1200000.000	1200000	28 years 03 months 25 days	01 Years 08 Months 14 Days (Jun 30, 2022)	...	0.670	nan	nan	2.000	1.000	nan	nan	0.200	0.400	232 days
9496	/jumplist/transfers/spieler/650245/transfer_id...	3104083	650245	1	25000.000	0	NaN	0	19 years 05 months 19 days	NaN	...	0.000	nan	nan	1.000	nan	nan	nan	nan	0.200	369 days
9497	/jumplist/transfers/spieler/333680/transfer_id...	3105139	333680	3	200000.000	0	NaN	0	25 years 02 months 23 days	02 Years 07 Months 14 Days (May 31, 2023)	...	0.000	nan	nan	1.000	nan	nan	nan	nan	0.200	255 days
9498	/jumplist/transfers/spieler/447112/transfer_id...	3105032	447112	1	NaN	0	NaN	0	22 years 09 months 02 days	08 Months 13 Days (Jun 30, 2021)	...	0.000	nan	nan	nan	1.000	nan	nan	0.200	nan	339 days

5 rows × 440 columns

df.describe()

	Total_Achievements	Distinct_Achievements	match_date_National_30	starting_lineup_National_30	matches_played_flag_National_30	goals_National_30	assists_National_30	own_goals_National_30	yellow_card_flag_National_30	second_yellow_card_flag_National_30	...	points_not_played_coverage_5	Injury_5	Suspension_5	not in squad_5	on the bench _5	injury_rate_5	suspension_rate_5	on_the_bench_rate_5	not_in_squad_rate_5	last_played_game_recency_5
count	4199.000	4199.000	6534.000	6534.000	6534.000	6534.000	6534.000	6534.000	6534.000	6534.000	...	6216.000	655.000	563.000	3719.000	2456.000	655.000	563.000	2456.000	3719.000	9381
mean	2.881	2.101	20.697	7.839	10.535	1.456	0.795	0.017	1.038	0.026	...	0.473	2.643	1.272	2.136	1.795	0.529	0.254	0.360	0.428	79 days 08:39:26.997121842
std	3.061	1.580	10.674	6.674	7.515	2.519	1.449	0.131	1.420	0.164	...	0.347	1.507	0.806	1.390	1.085	0.301	0.161	0.218	0.278	56 days 05:10:28.867578256
min	1.000	1.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	...	0.000	1.000	1.000	1.000	1.000	0.200	0.200	0.200	0.200	3 days 00:00:00
25%	1.000	1.000	11.000	2.000	4.000	0.000	0.000	0.000	0.000	0.000	...	0.170	1.000	1.000	1.000	1.000	0.200	0.200	0.200	0.200	50 days 00:00:00
50%	2.000	2.000	27.000	6.000	10.000	0.000	0.000	0.000	1.000	0.000	...	0.470	2.000	1.000	2.000	1.000	0.400	0.200	0.200	0.400	71 days 00:00:00
75%	3.000	3.000	30.000	12.000	16.000	2.000	1.000	0.000	2.000	0.000	...	0.750	4.000	1.000	3.000	2.000	0.800	0.200	0.400	0.600	95 days 00:00:00
max	71.000	19.000	30.000	30.000	30.000	25.000	18.000	3.000	11.000	2.000	...	1.000	5.000	5.000	5.000	5.000	1.000	1.000	1.000	1.000	909 days 00:00:00

8 rows × 402 columns

1. How many players are in the data in each season? (2016-2020)

season_count=df.Transfer_Season.value_counts()

#Horizontal bar plot
ax=season_count.plot.barh(figsize=(10,5), fontsize=11,color='darkblue')
ax.set_alpha(0.1)
ax.set_title("Transfer Fee & Season", fontsize=13)
ax.set_ylabel("Season", fontsize=13);
plt.show()

2. What is the average fee in each year?

num_replace = {
    'k' : 1000,
    'm' : 1000000
}

def pure_number(s):
    """ A function to return string variable which contains m., k. abbreavations to represent million and thousand to float
    Input: 
        String variable with abbrevations m or k i.e "1.3 m" ,"138 k"
    Output:
        Numeric value of string variable with abbrevations handled.
    """
    mult = 1.0
    while s[-1] in num_replace:
        mult *= num_replace[s[-1]]
        s = s[:-1]
    return round(float(s) * mult)

#Formatting fee as numeric
df=df[(df['Fee'] != 'Free transfer')]
df['Fee2']=df['Fee'].str.replace('Th.','k').str.replace('€','').str.replace('-','0')
df['Fee_Money']= [pure_number(x) for x in df['Fee2']]

fee_graph=df.groupby(by='Transfer_Season')['Fee_Money'].agg('mean').sort_values(ascending=True)

ax=fee_graph.plot.barh(figsize=(10,5), fontsize=11,color='grey')
ax.set_alpha(0.1)
ax.set_title("Transfer Fee & Season Avg Fee", fontsize=13)
ax.set_ylabel("Season", fontsize=13);
plt.show()

4. What is the average value of positions?

fig = px.pie(df, names='Main_position')
fig.show()

4. What is the average fee in each positions?

value=df.groupby(by='Main_position')['Fee_Money'].agg('mean').sort_values(ascending=True)

ax=value.plot.barh(figsize=(15,7), fontsize=13,color='darkblue')
ax.set_alpha(0.1)
ax.set_title("Transfer Fee & Position", fontsize=18)
ax.set_ylabel("Position", fontsize=15);
plt.show()

Data Preprocessing

Let's explore the dataset a little bit. How many players exist in each position? Let's use team_position field first to find answers to our questions.

1. Number of days since last played

Some time difference features created in national stats and stats section have timedelta64 data type. In the below, i get the "days" from the data.

df['last_played_game_recency_National_30']=df['last_played_game_recency_National_30'].astype('timedelta64[D]')
df['last_played_game_recency_National_20']=df['last_played_game_recency_National_20'].astype('timedelta64[D]')
df['last_played_game_recency_National_10']=df['last_played_game_recency_National_10'].astype('timedelta64[D]')
df['last_played_game_recency_National_5']=df['last_played_game_recency_National_5'].astype('timedelta64[D]')
df['last_played_game_recency_30']=df['last_played_game_recency_30'].astype('timedelta64[D]')
df['last_played_game_recency_20']=df['last_played_game_recency_20'].astype('timedelta64[D]')
df['last_played_game_recency_10']=df['last_played_game_recency_10'].astype('timedelta64[D]')
df['last_played_game_recency_5']=df['last_played_game_recency_5'].astype('timedelta64[D]')

2. Foot

In the dataset, foot is specified as categorical variable. I am going to create dummy variables for foot which will give if the player is left footed, right footed or use both.

df['Foot'].value_counts()

right    6622
left     2363
both      512
Name: Foot, dtype: int64

foot_dummies=pd.get_dummies(df.Foot)

3.Main Positions

Main position of a football player is categorical, i will get dummy variables for each main position.

df['Main_position'].value_counts()

Centre-Forward        1892
Centre-Back           1506
Central Midfield      1083
Left Winger            827
Defensive Midfield     784
Right Winger           727
Attacking Midfield     686
Left-Back              626
Goalkeeper             522
Right-Back             518
Left Midfield          122
Right Midfield         107
Second Striker          97
Name: Main_position, dtype: int64

main_position_dummies=pd.get_dummies(df.Main_position)

4.NOF Positions

In the profile dataset, positions footballer can play is specified as main position, other position1 and other position2. I created a new variable as number of positions by using those fields.Every football player has main position but, some football players can playin multiple positions.

sum(df['Main_position']=='')

0

sum(df['other_position1']=='')

2152

sum(df['other_position2']=='')

4463

df['NOF_position'] = [len( [a  for a in [x,y,z] if a]) for x,y,z in zip(df['Main_position'],df['other_position1'],df['other_position2'])]

5.Country Left and Country Joined

In each transfer, country left and country joined fields are available. I will define a threshold 50 and get dummy variable for each field if value count of country is greater than threshold.Below 50 is gathered to be "uncommon" field.

df['Country_Left'].unique()

array(['Germany', 'Mexico', 'China', 'Brazil', 'Italy', 'Argentina', nan,
       'Slovenia', 'Colombia', 'Uruguay', 'Spain', 'Belgium',
       'Korea, South', 'Norway', 'Sweden', 'France', 'Japan', 'Croatia',
       'Ukraine', 'Czech Republic', 'Austria', 'Greece', 'Belarus',
       'Kazakhstan', 'Australia', 'Portugal', 'Georgia', 'Thailand',
       'Switzerland', 'Israel', 'Albania', 'Peru', 'Iceland', 'Lithuania',
       'Netherlands', 'Romania', 'Poland', 'Russia', 'England', 'Egypt',
       'Uzbekistan', 'Bulgaria', 'United States', 'Venezuela', 'Turkey',
       'Algeria', 'Serbia', 'Cyprus', 'Morocco', 'Denmark', 'Costa Rica',
       'Tunisia', 'Hungary', 'Slovakia', 'Montenegro', 'Finland',
       'Bosnia-Herzegovina', 'Chile', 'Ecuador', 'South Africa',
       'Scotland', 'United Arab Emirates', 'Iran', 'Moldova', 'Latvia',
       'Saudi Arabia', 'Vietnam', 'Malta', 'Ghana', 'Azerbaijan',
       'Luxembourg', 'Qatar', 'Lebanon', 'Malaysia', 'Paraguay',
       'Hongkong', 'Estonia', 'India', 'North Macedonia', 'Nigeria',
       'Ireland', 'Singapore', 'Armenia', 'Indonesia', 'Kosovo', 'Canada',
       'Tajikistan'], dtype=object)

threshold = 50
counts = df.Country_Left.value_counts()
repl = counts[counts <= threshold].index
country_left_dummies=pd.get_dummies(df.Country_Left.replace(repl, 'uncommon'))
country_left_dummies=country_left_dummies.add_suffix('_c_left')

df['Country_Joined'].unique()

array(['Germany', 'Mexico', 'China', 'Switzerland', 'Spain', 'Brazil',
       'Argentina', 'Denmark', 'Portugal', 'France', 'Netherlands',
       'Belgium', nan, 'Japan', 'Czech Republic', 'Greece', 'Russia',
       'Korea, South', 'Italy', 'Thailand', 'Romania', 'Peru', 'Norway',
       'Belarus', 'Sweden', 'Poland', 'England', 'Egypt', 'Uzbekistan',
       'Israel', 'United Arab Emirates', 'Turkey', 'Saudi Arabia',
       'Algeria', 'Serbia', 'Austria', 'Bulgaria', 'Morocco',
       'Costa Rica', 'Tunisia', 'Slovenia', 'United States', 'Scotland',
       'Uruguay', 'Cyprus', 'Chile', 'Qatar', 'Lebanon', 'Croatia',
       'Ukraine', 'Albania', 'Hungary', 'Iceland', 'Ecuador', 'Slovakia',
       'Moldova', 'Colombia', 'Azerbaijan', 'Iran', 'Latvia',
       'Bosnia-Herzegovina', 'Luxembourg', 'Malta', 'South Africa',
       'Kazakhstan', 'Finland', 'Lithuania', 'Paraguay', 'Hongkong',
       'Malaysia', 'Georgia', 'India', 'Indonesia', 'North Macedonia',
       'Australia', 'Montenegro', 'Singapore', 'Venezuela', 'Tajikistan',
       'Armenia', 'Guatemala', 'Bangladesh', 'Kosovo'], dtype=object)

threshold = 50
counts = df.Country_Joined.value_counts()
repl = counts[counts <= threshold].index
country_joined_dummies=pd.get_dummies(df.Country_Joined.replace(repl, 'uncommon'))
country_joined_dummies=country_joined_dummies.add_suffix('_c_joined')

6.Contract Left at the time of transfer

In each transfer, fee of transfer should be highly correlated to the remaining contract time of footballers in the existing team. This value is given for some football players but format is need to be changed. I calculated remaining months of existing contract.

df['Contract_Left_at_Time_of_transfer']

0       02 Years 05 Months 29 Days  (Jun 30, 2018)
1                                              NaN
2       01 Years 11 Months 29 Days  (Dec 31, 2017)
3                11 Months 29 Days  (Dec 31, 2016)
4                                              NaN
                           ...                    
9494                                           NaN
9495    01 Years 08 Months 14 Days  (Jun 30, 2022)
9496                                           NaN
9497    02 Years 07 Months 14 Days  (May 31, 2023)
9498             08 Months 13 Days  (Jun 30, 2021)
Name: Contract_Left_at_Time_of_transfer, Length: 9497, dtype: object

7.Contract Left at the time of transfer

In each transfer, fee of transfer should be highly correlated to the remaining contract time of footballers in the existing team. This value is given for some football players but format is need to be changed. I calculated remaining months of existing contract.

aa=df['Contract_Left_at_Time_of_transfer'].str.split(' ',expand=True)
aa.columns = ['aa','bb','cc','dd','ee','ff','gg','hh','ii','jj']

aa.fillna(0,inplace=True)

df['months1']=[int(col1)*12 if col2 == 'Years' else 0 for col1,col2 in zip(aa['aa'],aa['bb'])]
df['months2']=[int(col1) if col2 == 'Months' else 0 for col1,col2 in zip(aa['aa'],aa['bb'])]
df['months3']=[int(col1) if col2 == 'Months' else 0 for col1,col2 in zip(aa['cc'],aa['dd'])]
df['remaining_contract_month']=df['months1']+df['months2']+df['months3']
df['Contract_Left_at_Time_of_transfer']=df['Contract_Left_at_Time_of_transfer'].fillna('Nan')
df['remaining_contract_month']= [x if y!= 'Nan' else np.nan for x,y in zip(df['remaining_contract_month'], df['Contract_Left_at_Time_of_transfer'])]
df.drop(['months1','months2','months3','Contract_Left_at_Time_of_transfer'],axis=1,inplace=True)

8.Age

Age field should be formatted to use in the model.

aa=df['Age_at_Time_of_transfer'].str.split(' ',expand=True)
aa.columns = ['aa','bb','cc','dd','ee','ff']

df['months1']=[int(col1)*12 if col2 == 'years' else 0 for col1,col2 in zip(aa['aa'],aa['bb'])]
df['months2']=[int(col1) if col2 == 'months' else 0 for col1,col2 in zip(aa['aa'],aa['bb'])]
df['months3']=[int(col1) if col2 == 'months' else 0 for col1,col2 in zip(aa['cc'],aa['dd'])]
df['Age_month']=df['months1']+df['months2']+df['months3']
df['Age_at_Time_of_transfer']=df['Age_at_Time_of_transfer'].fillna('Nan')
df['Age_month']= [x if y!= 'Nan' else np.nan for x,y in zip(df['Age_month'], df['Age_at_Time_of_transfer'])]

df.drop(['months1','months2','months3','Age_at_Time_of_transfer'],axis=1,inplace=True)

9.Height

Height field should be changed and formatted to be float.

df['Height'] = [float(x.replace('m','').replace(',','.'))*100 for x in df['Height'] ]

10.Market Value at the time of transfer

Market value at the time of the transfer should be formatted

df['Market_Value_at_Time_of_transfer2']=df['Market_Value_at_Time_of_transfer'].str.replace('Th.','k').str.replace('€','').str.replace('-','0')

df['Market_Value_Money']= [pure_number(x) for x in df['Market_Value_at_Time_of_transfer2']]

11.Fee

Fee is the target variable, should be float

df['Fee']

0        €8.00m
1        €7.30m
2        €7.05m
3        €6.25m
4        €5.50m
         ...   
9494    €278Th.
9495    €100Th.
9496     €35Th.
9497    €186Th.
9498     €35Th.
Name: Fee, Length: 9497, dtype: object

df['Fee2']=df['Fee'].str.replace('Th.','k').str.replace('€','').str.replace('-','0')

df['Fee_Money']= [pure_number(x) for x in df['Fee2']]

Merge Dummy Variables and Drop Unnecessary Fields

Some columns are removed not to use in prediction.

df=df.merge(country_joined_dummies,left_index=True,right_index=True)
df=df.merge(country_left_dummies,left_index=True,right_index=True)
df=df.merge(main_position_dummies,left_index=True,right_index=True)
df=df.merge(foot_dummies,left_index=True,right_index=True)

df.drop(['Transfer_Link_x','Country_Left','Country_Joined','Foot','Main_position',
'Transfer_id',
'id_x',
'Avg_Market_Value',
'Tot_Fee_Loan_Fee_Inc',
'Market_Value_at_Time_of_transfer',
'Market_Value_at_Time_of_transfer2',
'Team_Left_Tier',
'Team_Joined_Tier',
'Team_Left_League',
'Team_Joined_League',
'Fee',
'Transfer_Season',
'Transfer_Date_x',
'Team_Left',
'Team_Joined',
'Fee2',
'Transfer_Link_y',
'id_y',
'Transfer_Date_y',
'Date_of_birth',
'Place_of_birth',
'Position','other_position1',
'other_position2','Citizenship'],axis=1,inplace=True)

Modelling: Predicting Transfer Fee

Let's try to predict the value of the players using the features. I will use LightGBM and Keras for prediction. After i will compare the results of these 2 algorithms

Prediction of the Transfer Fee : LightGBM Regressor

LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed and efficient with the following advantages:

• Faster training speed and higher efficiency.

• Lower memory usage.

• Better accuracy.

• Support of parallel and GPU learning.

• Capable of handling large-scale data.

Leaf-wise (Best-first) Tree Growth

Most decision tree learning algorithms grow trees by level (depth)-wise, like the following image:

LightGBM grows trees leaf-wise. It will choose the leaf with max delta loss to grow. Holding #leaf fixed, leaf-wise algorithms tend to achieve lower loss than level-wise algorithms.

Leaf-wise may cause over-fitting when data is small, so LightGBM includes the max_depth parameter to limit tree depth. However, trees still grow leaf-wise even when max_depth is specified.

Source : LightGBM

# Define X ,y values
y=df['Fee_Money']
X=df.drop(['Fee_Money'],axis=1)

# Create training and test sets
x_train2, x_test2, y_train2, y_test2 = train_test_split(X, y, test_size=0.3, random_state=1907)

# LGBM wants this
x_train=x_train2.values
x_test=x_test2.values
y_train=y_train2.values
y_test=y_test2.values

#Instainsiate the model
model = LGBMRegressor(boosting_type='gbdt', objective='regression', metric='mae',bagging_fraction=0.8, 
                      feature_fraction=0.8, reg_lambda=0.9,n_estimators=400, importance_type='split')

#fit the model
model.fit(x_train, y_train,  eval_set= [(x_train, y_train), (x_test, y_test)],early_stopping_rounds=50)

[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	training's l1: 4.09265e+06	valid_1's l1: 3.87046e+06
Training until validation scores don't improve for 50 rounds
[2]	training's l1: 3.7606e+06	valid_1's l1: 3.56852e+06
[3]	training's l1: 3.46555e+06	valid_1's l1: 3.30301e+06
[4]	training's l1: 3.20847e+06	valid_1's l1: 3.06779e+06
[5]	training's l1: 2.98063e+06	valid_1's l1: 2.8648e+06
[6]	training's l1: 2.85553e+06	valid_1's l1: 2.76279e+06
[7]	training's l1: 2.74258e+06	valid_1's l1: 2.67871e+06
[8]	training's l1: 2.56817e+06	valid_1's l1: 2.52998e+06
[9]	training's l1: 2.41507e+06	valid_1's l1: 2.40292e+06
[10]	training's l1: 2.27937e+06	valid_1's l1: 2.29264e+06
[11]	training's l1: 2.15677e+06	valid_1's l1: 2.1944e+06
[12]	training's l1: 2.08419e+06	valid_1's l1: 2.14926e+06
[13]	training's l1: 1.98695e+06	valid_1's l1: 2.07216e+06
[14]	training's l1: 1.93416e+06	valid_1's l1: 2.03713e+06
[15]	training's l1: 1.85531e+06	valid_1's l1: 1.97767e+06
[16]	training's l1: 1.78167e+06	valid_1's l1: 1.92653e+06
[17]	training's l1: 1.71817e+06	valid_1's l1: 1.8813e+06
[18]	training's l1: 1.65884e+06	valid_1's l1: 1.8371e+06
[19]	training's l1: 1.60973e+06	valid_1's l1: 1.79843e+06
[20]	training's l1: 1.56753e+06	valid_1's l1: 1.76687e+06
[21]	training's l1: 1.52528e+06	valid_1's l1: 1.7405e+06
[22]	training's l1: 1.4878e+06	valid_1's l1: 1.71286e+06
[23]	training's l1: 1.45308e+06	valid_1's l1: 1.69197e+06
[24]	training's l1: 1.4228e+06	valid_1's l1: 1.67771e+06
[25]	training's l1: 1.39525e+06	valid_1's l1: 1.6631e+06
[26]	training's l1: 1.3705e+06	valid_1's l1: 1.64841e+06
[27]	training's l1: 1.34856e+06	valid_1's l1: 1.63778e+06
[28]	training's l1: 1.32594e+06	valid_1's l1: 1.62155e+06
[29]	training's l1: 1.30551e+06	valid_1's l1: 1.61245e+06
[30]	training's l1: 1.28489e+06	valid_1's l1: 1.60287e+06
[31]	training's l1: 1.2687e+06	valid_1's l1: 1.59332e+06
[32]	training's l1: 1.25253e+06	valid_1's l1: 1.58963e+06
[33]	training's l1: 1.23648e+06	valid_1's l1: 1.58648e+06
[34]	training's l1: 1.22151e+06	valid_1's l1: 1.58284e+06
[35]	training's l1: 1.20966e+06	valid_1's l1: 1.57955e+06
[36]	training's l1: 1.19568e+06	valid_1's l1: 1.57586e+06
[37]	training's l1: 1.18286e+06	valid_1's l1: 1.56937e+06
[38]	training's l1: 1.17238e+06	valid_1's l1: 1.56728e+06
[39]	training's l1: 1.15986e+06	valid_1's l1: 1.56503e+06
[40]	training's l1: 1.14846e+06	valid_1's l1: 1.55852e+06
[41]	training's l1: 1.13798e+06	valid_1's l1: 1.55699e+06
[42]	training's l1: 1.12858e+06	valid_1's l1: 1.55546e+06
[43]	training's l1: 1.11902e+06	valid_1's l1: 1.55295e+06
[44]	training's l1: 1.11146e+06	valid_1's l1: 1.55273e+06
[45]	training's l1: 1.10217e+06	valid_1's l1: 1.55046e+06
[46]	training's l1: 1.09474e+06	valid_1's l1: 1.55e+06
[47]	training's l1: 1.08697e+06	valid_1's l1: 1.54738e+06
[48]	training's l1: 1.07912e+06	valid_1's l1: 1.54724e+06
[49]	training's l1: 1.07346e+06	valid_1's l1: 1.54641e+06
[50]	training's l1: 1.06683e+06	valid_1's l1: 1.54413e+06
[51]	training's l1: 1.05901e+06	valid_1's l1: 1.54208e+06
[52]	training's l1: 1.05237e+06	valid_1's l1: 1.54174e+06
[53]	training's l1: 1.0466e+06	valid_1's l1: 1.54251e+06
[54]	training's l1: 1.03934e+06	valid_1's l1: 1.54114e+06
[55]	training's l1: 1.03251e+06	valid_1's l1: 1.53744e+06
[56]	training's l1: 1.02595e+06	valid_1's l1: 1.54073e+06
[57]	training's l1: 1.02098e+06	valid_1's l1: 1.54005e+06
[58]	training's l1: 1.01631e+06	valid_1's l1: 1.54025e+06
[59]	training's l1: 1.01082e+06	valid_1's l1: 1.53988e+06
[60]	training's l1: 1.00545e+06	valid_1's l1: 1.54041e+06
[61]	training's l1: 999219	valid_1's l1: 1.54233e+06
[62]	training's l1: 994663	valid_1's l1: 1.54357e+06
[63]	training's l1: 988863	valid_1's l1: 1.54391e+06
[64]	training's l1: 983400	valid_1's l1: 1.54294e+06
[65]	training's l1: 978609	valid_1's l1: 1.54279e+06
[66]	training's l1: 972493	valid_1's l1: 1.54256e+06
[67]	training's l1: 968064	valid_1's l1: 1.5433e+06
[68]	training's l1: 963471	valid_1's l1: 1.54376e+06
[69]	training's l1: 957988	valid_1's l1: 1.54515e+06
[70]	training's l1: 954486	valid_1's l1: 1.54563e+06
[71]	training's l1: 950138	valid_1's l1: 1.54615e+06
[72]	training's l1: 944728	valid_1's l1: 1.54676e+06
[73]	training's l1: 939990	valid_1's l1: 1.54707e+06
[74]	training's l1: 934899	valid_1's l1: 1.54719e+06
[75]	training's l1: 930746	valid_1's l1: 1.54744e+06
[76]	training's l1: 927513	valid_1's l1: 1.54795e+06
[77]	training's l1: 923624	valid_1's l1: 1.54815e+06
[78]	training's l1: 919157	valid_1's l1: 1.54791e+06
[79]	training's l1: 916241	valid_1's l1: 1.54725e+06
[80]	training's l1: 911020	valid_1's l1: 1.54706e+06
[81]	training's l1: 905939	valid_1's l1: 1.54664e+06
[82]	training's l1: 901920	valid_1's l1: 1.54784e+06
[83]	training's l1: 898171	valid_1's l1: 1.54858e+06
[84]	training's l1: 895049	valid_1's l1: 1.55025e+06
[85]	training's l1: 891216	valid_1's l1: 1.55166e+06
[86]	training's l1: 887022	valid_1's l1: 1.55144e+06
[87]	training's l1: 882286	valid_1's l1: 1.55046e+06
[88]	training's l1: 879978	valid_1's l1: 1.55191e+06
[89]	training's l1: 876304	valid_1's l1: 1.55214e+06
[90]	training's l1: 873016	valid_1's l1: 1.55417e+06
[91]	training's l1: 869207	valid_1's l1: 1.55418e+06
[92]	training's l1: 865129	valid_1's l1: 1.55425e+06
[93]	training's l1: 861907	valid_1's l1: 1.55552e+06
[94]	training's l1: 858334	valid_1's l1: 1.55645e+06
[95]	training's l1: 856034	valid_1's l1: 1.55706e+06
[96]	training's l1: 852584	valid_1's l1: 1.55974e+06
[97]	training's l1: 849070	valid_1's l1: 1.5602e+06
[98]	training's l1: 845514	valid_1's l1: 1.56083e+06
[99]	training's l1: 841920	valid_1's l1: 1.56151e+06
[100]	training's l1: 838767	valid_1's l1: 1.56121e+06
[101]	training's l1: 835467	valid_1's l1: 1.56228e+06
[102]	training's l1: 832438	valid_1's l1: 1.56194e+06
[103]	training's l1: 828735	valid_1's l1: 1.56172e+06
[104]	training's l1: 824175	valid_1's l1: 1.5616e+06
[105]	training's l1: 821446	valid_1's l1: 1.56244e+06
Early stopping, best iteration is:
[55]	training's l1: 1.03251e+06	valid_1's l1: 1.53744e+06

LGBMRegressor(bagging_fraction=0.8, feature_fraction=0.8, metric='mae',
              n_estimators=400, objective='regression', reg_lambda=0.9)

# Hyper paramter optimization : Grid Search
parameters = {'n_estimators': [400,800,1200],
              'learning_rate': [0.1, 0.2],
              'max_depth':[-1,5,6],
              'num_leaves' : [100,200]
             }
gridSearchCV = GridSearchCV(estimator = model, 
    param_grid = parameters, 
    scoring='neg_mean_absolute_error',
    n_jobs=1,
    iid=False, 
    verbose=1,
    cv=3)
gridSearchCV.fit(x_train,y_train,eval_set = (x_test, y_test),early_stopping_rounds=30)

Fitting 3 folds for each of 36 candidates, totalling 108 fits

[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.

[1]	valid_0's l1: 3.8804e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58147e+06
[3]	valid_0's l1: 3.31561e+06
[4]	valid_0's l1: 3.08939e+06
[5]	valid_0's l1: 2.89077e+06
[6]	valid_0's l1: 2.79162e+06
[7]	valid_0's l1: 2.70318e+06
[8]	valid_0's l1: 2.55683e+06
[9]	valid_0's l1: 2.42573e+06
[10]	valid_0's l1: 2.31887e+06
[11]	valid_0's l1: 2.22359e+06
[12]	valid_0's l1: 2.18024e+06
[13]	valid_0's l1: 2.09433e+06
[14]	valid_0's l1: 2.06667e+06
[15]	valid_0's l1: 2.0008e+06
[16]	valid_0's l1: 1.94363e+06
[17]	valid_0's l1: 1.89901e+06
[18]	valid_0's l1: 1.85718e+06
[19]	valid_0's l1: 1.81714e+06
[20]	valid_0's l1: 1.78493e+06
[21]	valid_0's l1: 1.75613e+06
[22]	valid_0's l1: 1.73142e+06
[23]	valid_0's l1: 1.71209e+06
[24]	valid_0's l1: 1.69322e+06
[25]	valid_0's l1: 1.67855e+06
[26]	valid_0's l1: 1.66736e+06
[27]	valid_0's l1: 1.66042e+06
[28]	valid_0's l1: 1.64903e+06
[29]	valid_0's l1: 1.64043e+06
[30]	valid_0's l1: 1.63364e+06
[31]	valid_0's l1: 1.62925e+06
[32]	valid_0's l1: 1.62312e+06
[33]	valid_0's l1: 1.62148e+06
[34]	valid_0's l1: 1.6214e+06
[35]	valid_0's l1: 1.61554e+06
[36]	valid_0's l1: 1.61147e+06
[37]	valid_0's l1: 1.61104e+06
[38]	valid_0's l1: 1.60897e+06
[39]	valid_0's l1: 1.61109e+06
[40]	valid_0's l1: 1.60755e+06
[41]	valid_0's l1: 1.60865e+06
[42]	valid_0's l1: 1.61138e+06
[43]	valid_0's l1: 1.61081e+06
[44]	valid_0's l1: 1.61109e+06
[45]	valid_0's l1: 1.61105e+06
[46]	valid_0's l1: 1.6129e+06
[47]	valid_0's l1: 1.61142e+06
[48]	valid_0's l1: 1.61223e+06
[49]	valid_0's l1: 1.61085e+06
[50]	valid_0's l1: 1.6142e+06
[51]	valid_0's l1: 1.61623e+06
[52]	valid_0's l1: 1.61796e+06
[53]	valid_0's l1: 1.6188e+06
[54]	valid_0's l1: 1.62176e+06
[55]	valid_0's l1: 1.62242e+06
[56]	valid_0's l1: 1.62088e+06
[57]	valid_0's l1: 1.62222e+06
[58]	valid_0's l1: 1.62347e+06
[59]	valid_0's l1: 1.62433e+06
[60]	valid_0's l1: 1.62428e+06
[61]	valid_0's l1: 1.6274e+06
[62]	valid_0's l1: 1.62864e+06
[63]	valid_0's l1: 1.62993e+06
[64]	valid_0's l1: 1.62965e+06
[65]	valid_0's l1: 1.63218e+06
[66]	valid_0's l1: 1.63269e+06
[67]	valid_0's l1: 1.63347e+06
[68]	valid_0's l1: 1.63408e+06
[69]	valid_0's l1: 1.63432e+06
[70]	valid_0's l1: 1.63412e+06
Early stopping, best iteration is:
[40]	valid_0's l1: 1.60755e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.82234e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.53738e+06
[3]	valid_0's l1: 3.28278e+06
[4]	valid_0's l1: 3.05055e+06
[5]	valid_0's l1: 2.85395e+06
[6]	valid_0's l1: 2.76027e+06
[7]	valid_0's l1: 2.67207e+06
[8]	valid_0's l1: 2.52479e+06
[9]	valid_0's l1: 2.39693e+06
[10]	valid_0's l1: 2.2844e+06
[11]	valid_0's l1: 2.18771e+06
[12]	valid_0's l1: 2.13956e+06
[13]	valid_0's l1: 2.06551e+06
[14]	valid_0's l1: 2.03037e+06
[15]	valid_0's l1: 1.97266e+06
[16]	valid_0's l1: 1.92277e+06
[17]	valid_0's l1: 1.88071e+06
[18]	valid_0's l1: 1.84012e+06
[19]	valid_0's l1: 1.80914e+06
[20]	valid_0's l1: 1.78341e+06
[21]	valid_0's l1: 1.75977e+06
[22]	valid_0's l1: 1.73938e+06
[23]	valid_0's l1: 1.71884e+06
[24]	valid_0's l1: 1.704e+06
[25]	valid_0's l1: 1.68982e+06
[26]	valid_0's l1: 1.67853e+06
[27]	valid_0's l1: 1.66707e+06
[28]	valid_0's l1: 1.6575e+06
[29]	valid_0's l1: 1.64879e+06
[30]	valid_0's l1: 1.64292e+06
[31]	valid_0's l1: 1.63945e+06
[32]	valid_0's l1: 1.6373e+06
[33]	valid_0's l1: 1.63527e+06
[34]	valid_0's l1: 1.63174e+06
[35]	valid_0's l1: 1.6321e+06
[36]	valid_0's l1: 1.62921e+06
[37]	valid_0's l1: 1.63137e+06
[38]	valid_0's l1: 1.62857e+06
[39]	valid_0's l1: 1.62869e+06
[40]	valid_0's l1: 1.62636e+06
[41]	valid_0's l1: 1.62635e+06
[42]	valid_0's l1: 1.62345e+06
[43]	valid_0's l1: 1.62422e+06
[44]	valid_0's l1: 1.62453e+06
[45]	valid_0's l1: 1.62611e+06
[46]	valid_0's l1: 1.6248e+06
[47]	valid_0's l1: 1.62704e+06
[48]	valid_0's l1: 1.62781e+06
[49]	valid_0's l1: 1.6272e+06
[50]	valid_0's l1: 1.62614e+06
[51]	valid_0's l1: 1.62683e+06
[52]	valid_0's l1: 1.62589e+06
[53]	valid_0's l1: 1.62841e+06
[54]	valid_0's l1: 1.62995e+06
[55]	valid_0's l1: 1.63114e+06
[56]	valid_0's l1: 1.63104e+06
[57]	valid_0's l1: 1.63222e+06
[58]	valid_0's l1: 1.63222e+06
[59]	valid_0's l1: 1.63304e+06
[60]	valid_0's l1: 1.63325e+06
[61]	valid_0's l1: 1.63288e+06
[62]	valid_0's l1: 1.63368e+06
[63]	valid_0's l1: 1.634e+06
[64]	valid_0's l1: 1.63577e+06
[65]	valid_0's l1: 1.63388e+06
[66]	valid_0's l1: 1.63492e+06
[67]	valid_0's l1: 1.63456e+06
[68]	valid_0's l1: 1.63418e+06
[69]	valid_0's l1: 1.63338e+06
[70]	valid_0's l1: 1.6334e+06
[71]	valid_0's l1: 1.63182e+06
[72]	valid_0's l1: 1.63426e+06
Early stopping, best iteration is:
[42]	valid_0's l1: 1.62345e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90331e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.60346e+06
[3]	valid_0's l1: 3.33147e+06
[4]	valid_0's l1: 3.0943e+06
[5]	valid_0's l1: 2.88691e+06
[6]	valid_0's l1: 2.77737e+06
[7]	valid_0's l1: 2.68585e+06
[8]	valid_0's l1: 2.53803e+06
[9]	valid_0's l1: 2.4083e+06
[10]	valid_0's l1: 2.29773e+06
[11]	valid_0's l1: 2.19713e+06
[12]	valid_0's l1: 2.14466e+06
[13]	valid_0's l1: 2.06369e+06
[14]	valid_0's l1: 2.03015e+06
[15]	valid_0's l1: 1.97551e+06
[16]	valid_0's l1: 1.92629e+06
[17]	valid_0's l1: 1.88563e+06
[18]	valid_0's l1: 1.84773e+06
[19]	valid_0's l1: 1.81126e+06
[20]	valid_0's l1: 1.7812e+06
[21]	valid_0's l1: 1.75382e+06
[22]	valid_0's l1: 1.73287e+06
[23]	valid_0's l1: 1.71452e+06
[24]	valid_0's l1: 1.69565e+06
[25]	valid_0's l1: 1.68183e+06
[26]	valid_0's l1: 1.667e+06
[27]	valid_0's l1: 1.6531e+06
[28]	valid_0's l1: 1.64525e+06
[29]	valid_0's l1: 1.63498e+06
[30]	valid_0's l1: 1.62945e+06
[31]	valid_0's l1: 1.62718e+06
[32]	valid_0's l1: 1.61879e+06
[33]	valid_0's l1: 1.61602e+06
[34]	valid_0's l1: 1.6127e+06
[35]	valid_0's l1: 1.60762e+06
[36]	valid_0's l1: 1.60376e+06
[37]	valid_0's l1: 1.60473e+06
[38]	valid_0's l1: 1.60411e+06
[39]	valid_0's l1: 1.6067e+06
[40]	valid_0's l1: 1.60682e+06
[41]	valid_0's l1: 1.60711e+06
[42]	valid_0's l1: 1.60511e+06
[43]	valid_0's l1: 1.60621e+06
[44]	valid_0's l1: 1.60682e+06
[45]	valid_0's l1: 1.60734e+06
[46]	valid_0's l1: 1.60853e+06
[47]	valid_0's l1: 1.61095e+06
[48]	valid_0's l1: 1.61156e+06
[49]	valid_0's l1: 1.61278e+06
[50]	valid_0's l1: 1.61521e+06
[51]	valid_0's l1: 1.61715e+06
[52]	valid_0's l1: 1.61574e+06
[53]	valid_0's l1: 1.61809e+06
[54]	valid_0's l1: 1.61949e+06
[55]	valid_0's l1: 1.61926e+06
[56]	valid_0's l1: 1.61998e+06
[57]	valid_0's l1: 1.62428e+06
[58]	valid_0's l1: 1.62571e+06
[59]	valid_0's l1: 1.62745e+06
[60]	valid_0's l1: 1.6269e+06
[61]	valid_0's l1: 1.62842e+06
[62]	valid_0's l1: 1.62883e+06
[63]	valid_0's l1: 1.62782e+06
[64]	valid_0's l1: 1.62625e+06
[65]	valid_0's l1: 1.62601e+06
[66]	valid_0's l1: 1.6253e+06
Early stopping, best iteration is:
[36]	valid_0's l1: 1.60376e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.88063e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58111e+06
[3]	valid_0's l1: 3.31471e+06
[4]	valid_0's l1: 3.08971e+06
[5]	valid_0's l1: 2.89137e+06
[6]	valid_0's l1: 2.79091e+06
[7]	valid_0's l1: 2.7016e+06
[8]	valid_0's l1: 2.5545e+06
[9]	valid_0's l1: 2.42672e+06
[10]	valid_0's l1: 2.31773e+06
[11]	valid_0's l1: 2.22329e+06
[12]	valid_0's l1: 2.17855e+06
[13]	valid_0's l1: 2.09992e+06
[14]	valid_0's l1: 2.07693e+06
[15]	valid_0's l1: 2.00991e+06
[16]	valid_0's l1: 1.95164e+06
[17]	valid_0's l1: 1.90423e+06
[18]	valid_0's l1: 1.86449e+06
[19]	valid_0's l1: 1.82493e+06
[20]	valid_0's l1: 1.79157e+06
[21]	valid_0's l1: 1.75899e+06
[22]	valid_0's l1: 1.7361e+06
[23]	valid_0's l1: 1.71289e+06
[24]	valid_0's l1: 1.69566e+06
[25]	valid_0's l1: 1.68045e+06
[26]	valid_0's l1: 1.66649e+06
[27]	valid_0's l1: 1.65602e+06
[28]	valid_0's l1: 1.65022e+06
[29]	valid_0's l1: 1.64358e+06
[30]	valid_0's l1: 1.63472e+06
[31]	valid_0's l1: 1.63274e+06
[32]	valid_0's l1: 1.62521e+06
[33]	valid_0's l1: 1.6268e+06
[34]	valid_0's l1: 1.62937e+06
[35]	valid_0's l1: 1.62197e+06
[36]	valid_0's l1: 1.62251e+06
[37]	valid_0's l1: 1.61791e+06
[38]	valid_0's l1: 1.6191e+06
[39]	valid_0's l1: 1.62166e+06
[40]	valid_0's l1: 1.61971e+06
[41]	valid_0's l1: 1.62036e+06
[42]	valid_0's l1: 1.62022e+06
[43]	valid_0's l1: 1.62122e+06
[44]	valid_0's l1: 1.62306e+06
[45]	valid_0's l1: 1.62404e+06
[46]	valid_0's l1: 1.62464e+06
[47]	valid_0's l1: 1.62581e+06
[48]	valid_0's l1: 1.6233e+06
[49]	valid_0's l1: 1.62433e+06
[50]	valid_0's l1: 1.62647e+06
[51]	valid_0's l1: 1.62283e+06
[52]	valid_0's l1: 1.62738e+06
[53]	valid_0's l1: 1.62974e+06
[54]	valid_0's l1: 1.63427e+06
[55]	valid_0's l1: 1.63703e+06
[56]	valid_0's l1: 1.63911e+06
[57]	valid_0's l1: 1.6396e+06
[58]	valid_0's l1: 1.63766e+06
[59]	valid_0's l1: 1.64045e+06
[60]	valid_0's l1: 1.64282e+06
[61]	valid_0's l1: 1.64267e+06
[62]	valid_0's l1: 1.64467e+06
[63]	valid_0's l1: 1.64473e+06
[64]	valid_0's l1: 1.64545e+06
[65]	valid_0's l1: 1.64774e+06
[66]	valid_0's l1: 1.64728e+06
[67]	valid_0's l1: 1.64694e+06
Early stopping, best iteration is:
[37]	valid_0's l1: 1.61791e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.82314e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.53885e+06
[3]	valid_0's l1: 3.28346e+06
[4]	valid_0's l1: 3.05156e+06
[5]	valid_0's l1: 2.85542e+06
[6]	valid_0's l1: 2.75925e+06
[7]	valid_0's l1: 2.66959e+06
[8]	valid_0's l1: 2.52656e+06
[9]	valid_0's l1: 2.40248e+06
[10]	valid_0's l1: 2.29316e+06
[11]	valid_0's l1: 2.1974e+06
[12]	valid_0's l1: 2.15027e+06
[13]	valid_0's l1: 2.07389e+06
[14]	valid_0's l1: 2.04006e+06
[15]	valid_0's l1: 1.98279e+06
[16]	valid_0's l1: 1.93007e+06
[17]	valid_0's l1: 1.88619e+06
[18]	valid_0's l1: 1.84794e+06
[19]	valid_0's l1: 1.8186e+06
[20]	valid_0's l1: 1.78666e+06
[21]	valid_0's l1: 1.76808e+06
[22]	valid_0's l1: 1.75232e+06
[23]	valid_0's l1: 1.73378e+06
[24]	valid_0's l1: 1.71863e+06
[25]	valid_0's l1: 1.70628e+06
[26]	valid_0's l1: 1.69601e+06
[27]	valid_0's l1: 1.68197e+06
[28]	valid_0's l1: 1.67391e+06
[29]	valid_0's l1: 1.66586e+06
[30]	valid_0's l1: 1.66154e+06
[31]	valid_0's l1: 1.65638e+06
[32]	valid_0's l1: 1.65255e+06
[33]	valid_0's l1: 1.65111e+06
[34]	valid_0's l1: 1.65118e+06
[35]	valid_0's l1: 1.64782e+06
[36]	valid_0's l1: 1.64348e+06
[37]	valid_0's l1: 1.64234e+06
[38]	valid_0's l1: 1.6437e+06
[39]	valid_0's l1: 1.64265e+06
[40]	valid_0's l1: 1.64379e+06
[41]	valid_0's l1: 1.64313e+06
[42]	valid_0's l1: 1.6418e+06
[43]	valid_0's l1: 1.64361e+06
[44]	valid_0's l1: 1.64218e+06
[45]	valid_0's l1: 1.64402e+06
[46]	valid_0's l1: 1.64146e+06
[47]	valid_0's l1: 1.64262e+06
[48]	valid_0's l1: 1.64187e+06
[49]	valid_0's l1: 1.64002e+06
[50]	valid_0's l1: 1.63854e+06
[51]	valid_0's l1: 1.63858e+06
[52]	valid_0's l1: 1.63825e+06
[53]	valid_0's l1: 1.64072e+06
[54]	valid_0's l1: 1.64255e+06
[55]	valid_0's l1: 1.64161e+06
[56]	valid_0's l1: 1.64266e+06
[57]	valid_0's l1: 1.64504e+06
[58]	valid_0's l1: 1.64487e+06
[59]	valid_0's l1: 1.64461e+06
[60]	valid_0's l1: 1.6457e+06
[61]	valid_0's l1: 1.64668e+06
[62]	valid_0's l1: 1.64771e+06
[63]	valid_0's l1: 1.64831e+06
[64]	valid_0's l1: 1.64711e+06
[65]	valid_0's l1: 1.64739e+06
[66]	valid_0's l1: 1.6483e+06
[67]	valid_0's l1: 1.64816e+06
[68]	valid_0's l1: 1.64978e+06
[69]	valid_0's l1: 1.65005e+06
[70]	valid_0's l1: 1.65012e+06
[71]	valid_0's l1: 1.65122e+06
[72]	valid_0's l1: 1.6506e+06
[73]	valid_0's l1: 1.6509e+06
[74]	valid_0's l1: 1.6501e+06
[75]	valid_0's l1: 1.65227e+06
[76]	valid_0's l1: 1.65293e+06
[77]	valid_0's l1: 1.65491e+06
[78]	valid_0's l1: 1.65499e+06
[79]	valid_0's l1: 1.65567e+06
[80]	valid_0's l1: 1.65697e+06
[81]	valid_0's l1: 1.65648e+06
[82]	valid_0's l1: 1.65633e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.63825e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90347e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.60447e+06
[3]	valid_0's l1: 3.33163e+06
[4]	valid_0's l1: 3.09336e+06
[5]	valid_0's l1: 2.88614e+06
[6]	valid_0's l1: 2.77812e+06
[7]	valid_0's l1: 2.68595e+06
[8]	valid_0's l1: 2.53776e+06
[9]	valid_0's l1: 2.40858e+06
[10]	valid_0's l1: 2.29804e+06
[11]	valid_0's l1: 2.20018e+06
[12]	valid_0's l1: 2.14893e+06
[13]	valid_0's l1: 2.07158e+06
[14]	valid_0's l1: 2.03795e+06
[15]	valid_0's l1: 1.98575e+06
[16]	valid_0's l1: 1.93925e+06
[17]	valid_0's l1: 1.89833e+06
[18]	valid_0's l1: 1.85799e+06
[19]	valid_0's l1: 1.81604e+06
[20]	valid_0's l1: 1.78718e+06
[21]	valid_0's l1: 1.76339e+06
[22]	valid_0's l1: 1.73882e+06
[23]	valid_0's l1: 1.71904e+06
[24]	valid_0's l1: 1.70315e+06
[25]	valid_0's l1: 1.68543e+06
[26]	valid_0's l1: 1.67107e+06
[27]	valid_0's l1: 1.66136e+06
[28]	valid_0's l1: 1.65118e+06
[29]	valid_0's l1: 1.64208e+06
[30]	valid_0's l1: 1.63366e+06
[31]	valid_0's l1: 1.63059e+06
[32]	valid_0's l1: 1.62535e+06
[33]	valid_0's l1: 1.62527e+06
[34]	valid_0's l1: 1.62184e+06
[35]	valid_0's l1: 1.62203e+06
[36]	valid_0's l1: 1.62009e+06
[37]	valid_0's l1: 1.61825e+06
[38]	valid_0's l1: 1.61759e+06
[39]	valid_0's l1: 1.61438e+06
[40]	valid_0's l1: 1.61596e+06
[41]	valid_0's l1: 1.61631e+06
[42]	valid_0's l1: 1.61543e+06
[43]	valid_0's l1: 1.61522e+06
[44]	valid_0's l1: 1.61456e+06
[45]	valid_0's l1: 1.61175e+06
[46]	valid_0's l1: 1.61233e+06
[47]	valid_0's l1: 1.61393e+06
[48]	valid_0's l1: 1.61366e+06
[49]	valid_0's l1: 1.61534e+06
[50]	valid_0's l1: 1.61645e+06
[51]	valid_0's l1: 1.61485e+06
[52]	valid_0's l1: 1.61601e+06
[53]	valid_0's l1: 1.61818e+06
[54]	valid_0's l1: 1.61939e+06
[55]	valid_0's l1: 1.61976e+06
[56]	valid_0's l1: 1.61974e+06
[57]	valid_0's l1: 1.62078e+06
[58]	valid_0's l1: 1.62052e+06
[59]	valid_0's l1: 1.62096e+06
[60]	valid_0's l1: 1.61909e+06
[61]	valid_0's l1: 1.62111e+06
[62]	valid_0's l1: 1.62204e+06
[63]	valid_0's l1: 1.624e+06
[64]	valid_0's l1: 1.62425e+06
[65]	valid_0's l1: 1.62319e+06
[66]	valid_0's l1: 1.6254e+06
[67]	valid_0's l1: 1.62587e+06
[68]	valid_0's l1: 1.6266e+06
[69]	valid_0's l1: 1.62549e+06
[70]	valid_0's l1: 1.62726e+06
[71]	valid_0's l1: 1.62715e+06
[72]	valid_0's l1: 1.62843e+06
[73]	valid_0's l1: 1.631e+06
[74]	valid_0's l1: 1.62983e+06
[75]	valid_0's l1: 1.63112e+06
Early stopping, best iteration is:
[45]	valid_0's l1: 1.61175e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.8804e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58147e+06
[3]	valid_0's l1: 3.31561e+06
[4]	valid_0's l1: 3.08939e+06
[5]	valid_0's l1: 2.89077e+06
[6]	valid_0's l1: 2.79162e+06
[7]	valid_0's l1: 2.70318e+06
[8]	valid_0's l1: 2.55683e+06
[9]	valid_0's l1: 2.42573e+06
[10]	valid_0's l1: 2.31887e+06
[11]	valid_0's l1: 2.22359e+06
[12]	valid_0's l1: 2.18024e+06
[13]	valid_0's l1: 2.09433e+06
[14]	valid_0's l1: 2.06667e+06
[15]	valid_0's l1: 2.0008e+06
[16]	valid_0's l1: 1.94363e+06
[17]	valid_0's l1: 1.89901e+06
[18]	valid_0's l1: 1.85718e+06
[19]	valid_0's l1: 1.81714e+06
[20]	valid_0's l1: 1.78493e+06
[21]	valid_0's l1: 1.75613e+06
[22]	valid_0's l1: 1.73142e+06
[23]	valid_0's l1: 1.71209e+06
[24]	valid_0's l1: 1.69322e+06
[25]	valid_0's l1: 1.67855e+06
[26]	valid_0's l1: 1.66736e+06
[27]	valid_0's l1: 1.66042e+06
[28]	valid_0's l1: 1.64903e+06
[29]	valid_0's l1: 1.64043e+06
[30]	valid_0's l1: 1.63364e+06
[31]	valid_0's l1: 1.62925e+06
[32]	valid_0's l1: 1.62312e+06
[33]	valid_0's l1: 1.62148e+06
[34]	valid_0's l1: 1.6214e+06
[35]	valid_0's l1: 1.61554e+06
[36]	valid_0's l1: 1.61147e+06
[37]	valid_0's l1: 1.61104e+06
[38]	valid_0's l1: 1.60897e+06
[39]	valid_0's l1: 1.61109e+06
[40]	valid_0's l1: 1.60755e+06
[41]	valid_0's l1: 1.60865e+06
[42]	valid_0's l1: 1.61138e+06
[43]	valid_0's l1: 1.61081e+06
[44]	valid_0's l1: 1.61109e+06
[45]	valid_0's l1: 1.61105e+06
[46]	valid_0's l1: 1.6129e+06
[47]	valid_0's l1: 1.61142e+06
[48]	valid_0's l1: 1.61223e+06
[49]	valid_0's l1: 1.61085e+06
[50]	valid_0's l1: 1.6142e+06
[51]	valid_0's l1: 1.61623e+06
[52]	valid_0's l1: 1.61796e+06
[53]	valid_0's l1: 1.6188e+06
[54]	valid_0's l1: 1.62176e+06
[55]	valid_0's l1: 1.62242e+06
[56]	valid_0's l1: 1.62088e+06
[57]	valid_0's l1: 1.62222e+06
[58]	valid_0's l1: 1.62347e+06
[59]	valid_0's l1: 1.62433e+06
[60]	valid_0's l1: 1.62428e+06
[61]	valid_0's l1: 1.6274e+06
[62]	valid_0's l1: 1.62864e+06
[63]	valid_0's l1: 1.62993e+06
[64]	valid_0's l1: 1.62965e+06
[65]	valid_0's l1: 1.63218e+06
[66]	valid_0's l1: 1.63269e+06
[67]	valid_0's l1: 1.63347e+06
[68]	valid_0's l1: 1.63408e+06
[69]	valid_0's l1: 1.63432e+06
[70]	valid_0's l1: 1.63412e+06
Early stopping, best iteration is:
[40]	valid_0's l1: 1.60755e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.82234e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.53738e+06
[3]	valid_0's l1: 3.28278e+06
[4]	valid_0's l1: 3.05055e+06
[5]	valid_0's l1: 2.85395e+06
[6]	valid_0's l1: 2.76027e+06
[7]	valid_0's l1: 2.67207e+06
[8]	valid_0's l1: 2.52479e+06
[9]	valid_0's l1: 2.39693e+06
[10]	valid_0's l1: 2.2844e+06
[11]	valid_0's l1: 2.18771e+06
[12]	valid_0's l1: 2.13956e+06
[13]	valid_0's l1: 2.06551e+06
[14]	valid_0's l1: 2.03037e+06
[15]	valid_0's l1: 1.97266e+06
[16]	valid_0's l1: 1.92277e+06
[17]	valid_0's l1: 1.88071e+06
[18]	valid_0's l1: 1.84012e+06
[19]	valid_0's l1: 1.80914e+06
[20]	valid_0's l1: 1.78341e+06
[21]	valid_0's l1: 1.75977e+06
[22]	valid_0's l1: 1.73938e+06
[23]	valid_0's l1: 1.71884e+06
[24]	valid_0's l1: 1.704e+06
[25]	valid_0's l1: 1.68982e+06
[26]	valid_0's l1: 1.67853e+06
[27]	valid_0's l1: 1.66707e+06
[28]	valid_0's l1: 1.6575e+06
[29]	valid_0's l1: 1.64879e+06
[30]	valid_0's l1: 1.64292e+06
[31]	valid_0's l1: 1.63945e+06
[32]	valid_0's l1: 1.6373e+06
[33]	valid_0's l1: 1.63527e+06
[34]	valid_0's l1: 1.63174e+06
[35]	valid_0's l1: 1.6321e+06
[36]	valid_0's l1: 1.62921e+06
[37]	valid_0's l1: 1.63137e+06
[38]	valid_0's l1: 1.62857e+06
[39]	valid_0's l1: 1.62869e+06
[40]	valid_0's l1: 1.62636e+06
[41]	valid_0's l1: 1.62635e+06
[42]	valid_0's l1: 1.62345e+06
[43]	valid_0's l1: 1.62422e+06
[44]	valid_0's l1: 1.62453e+06
[45]	valid_0's l1: 1.62611e+06
[46]	valid_0's l1: 1.6248e+06
[47]	valid_0's l1: 1.62704e+06
[48]	valid_0's l1: 1.62781e+06
[49]	valid_0's l1: 1.6272e+06
[50]	valid_0's l1: 1.62614e+06
[51]	valid_0's l1: 1.62683e+06
[52]	valid_0's l1: 1.62589e+06
[53]	valid_0's l1: 1.62841e+06
[54]	valid_0's l1: 1.62995e+06
[55]	valid_0's l1: 1.63114e+06
[56]	valid_0's l1: 1.63104e+06
[57]	valid_0's l1: 1.63222e+06
[58]	valid_0's l1: 1.63222e+06
[59]	valid_0's l1: 1.63304e+06
[60]	valid_0's l1: 1.63325e+06
[61]	valid_0's l1: 1.63288e+06
[62]	valid_0's l1: 1.63368e+06
[63]	valid_0's l1: 1.634e+06
[64]	valid_0's l1: 1.63577e+06
[65]	valid_0's l1: 1.63388e+06
[66]	valid_0's l1: 1.63492e+06
[67]	valid_0's l1: 1.63456e+06
[68]	valid_0's l1: 1.63418e+06
[69]	valid_0's l1: 1.63338e+06
[70]	valid_0's l1: 1.6334e+06
[71]	valid_0's l1: 1.63182e+06
[72]	valid_0's l1: 1.63426e+06
Early stopping, best iteration is:
[42]	valid_0's l1: 1.62345e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90331e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.60346e+06
[3]	valid_0's l1: 3.33147e+06
[4]	valid_0's l1: 3.0943e+06
[5]	valid_0's l1: 2.88691e+06
[6]	valid_0's l1: 2.77737e+06
[7]	valid_0's l1: 2.68585e+06
[8]	valid_0's l1: 2.53803e+06
[9]	valid_0's l1: 2.4083e+06
[10]	valid_0's l1: 2.29773e+06
[11]	valid_0's l1: 2.19713e+06
[12]	valid_0's l1: 2.14466e+06
[13]	valid_0's l1: 2.06369e+06
[14]	valid_0's l1: 2.03015e+06
[15]	valid_0's l1: 1.97551e+06
[16]	valid_0's l1: 1.92629e+06
[17]	valid_0's l1: 1.88563e+06
[18]	valid_0's l1: 1.84773e+06
[19]	valid_0's l1: 1.81126e+06
[20]	valid_0's l1: 1.7812e+06
[21]	valid_0's l1: 1.75382e+06
[22]	valid_0's l1: 1.73287e+06
[23]	valid_0's l1: 1.71452e+06
[24]	valid_0's l1: 1.69565e+06
[25]	valid_0's l1: 1.68183e+06
[26]	valid_0's l1: 1.667e+06
[27]	valid_0's l1: 1.6531e+06
[28]	valid_0's l1: 1.64525e+06
[29]	valid_0's l1: 1.63498e+06
[30]	valid_0's l1: 1.62945e+06
[31]	valid_0's l1: 1.62718e+06
[32]	valid_0's l1: 1.61879e+06
[33]	valid_0's l1: 1.61602e+06
[34]	valid_0's l1: 1.6127e+06
[35]	valid_0's l1: 1.60762e+06
[36]	valid_0's l1: 1.60376e+06
[37]	valid_0's l1: 1.60473e+06
[38]	valid_0's l1: 1.60411e+06
[39]	valid_0's l1: 1.6067e+06
[40]	valid_0's l1: 1.60682e+06
[41]	valid_0's l1: 1.60711e+06
[42]	valid_0's l1: 1.60511e+06
[43]	valid_0's l1: 1.60621e+06
[44]	valid_0's l1: 1.60682e+06
[45]	valid_0's l1: 1.60734e+06
[46]	valid_0's l1: 1.60853e+06
[47]	valid_0's l1: 1.61095e+06
[48]	valid_0's l1: 1.61156e+06
[49]	valid_0's l1: 1.61278e+06
[50]	valid_0's l1: 1.61521e+06
[51]	valid_0's l1: 1.61715e+06
[52]	valid_0's l1: 1.61574e+06
[53]	valid_0's l1: 1.61809e+06
[54]	valid_0's l1: 1.61949e+06
[55]	valid_0's l1: 1.61926e+06
[56]	valid_0's l1: 1.61998e+06
[57]	valid_0's l1: 1.62428e+06
[58]	valid_0's l1: 1.62571e+06
[59]	valid_0's l1: 1.62745e+06
[60]	valid_0's l1: 1.6269e+06
[61]	valid_0's l1: 1.62842e+06
[62]	valid_0's l1: 1.62883e+06
[63]	valid_0's l1: 1.62782e+06
[64]	valid_0's l1: 1.62625e+06
[65]	valid_0's l1: 1.62601e+06
[66]	valid_0's l1: 1.6253e+06
Early stopping, best iteration is:
[36]	valid_0's l1: 1.60376e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.88063e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58111e+06
[3]	valid_0's l1: 3.31471e+06
[4]	valid_0's l1: 3.08971e+06
[5]	valid_0's l1: 2.89137e+06
[6]	valid_0's l1: 2.79091e+06
[7]	valid_0's l1: 2.7016e+06
[8]	valid_0's l1: 2.5545e+06
[9]	valid_0's l1: 2.42672e+06
[10]	valid_0's l1: 2.31773e+06
[11]	valid_0's l1: 2.22329e+06
[12]	valid_0's l1: 2.17855e+06
[13]	valid_0's l1: 2.09992e+06
[14]	valid_0's l1: 2.07693e+06
[15]	valid_0's l1: 2.00991e+06
[16]	valid_0's l1: 1.95164e+06
[17]	valid_0's l1: 1.90423e+06
[18]	valid_0's l1: 1.86449e+06
[19]	valid_0's l1: 1.82493e+06
[20]	valid_0's l1: 1.79157e+06
[21]	valid_0's l1: 1.75899e+06
[22]	valid_0's l1: 1.7361e+06
[23]	valid_0's l1: 1.71289e+06
[24]	valid_0's l1: 1.69566e+06
[25]	valid_0's l1: 1.68045e+06
[26]	valid_0's l1: 1.66649e+06
[27]	valid_0's l1: 1.65602e+06
[28]	valid_0's l1: 1.65022e+06
[29]	valid_0's l1: 1.64358e+06
[30]	valid_0's l1: 1.63472e+06
[31]	valid_0's l1: 1.63274e+06
[32]	valid_0's l1: 1.62521e+06
[33]	valid_0's l1: 1.6268e+06
[34]	valid_0's l1: 1.62937e+06
[35]	valid_0's l1: 1.62197e+06
[36]	valid_0's l1: 1.62251e+06
[37]	valid_0's l1: 1.61791e+06
[38]	valid_0's l1: 1.6191e+06
[39]	valid_0's l1: 1.62166e+06
[40]	valid_0's l1: 1.61971e+06
[41]	valid_0's l1: 1.62036e+06
[42]	valid_0's l1: 1.62022e+06
[43]	valid_0's l1: 1.62122e+06
[44]	valid_0's l1: 1.62306e+06
[45]	valid_0's l1: 1.62404e+06
[46]	valid_0's l1: 1.62464e+06
[47]	valid_0's l1: 1.62581e+06
[48]	valid_0's l1: 1.6233e+06
[49]	valid_0's l1: 1.62433e+06
[50]	valid_0's l1: 1.62647e+06
[51]	valid_0's l1: 1.62283e+06
[52]	valid_0's l1: 1.62738e+06
[53]	valid_0's l1: 1.62974e+06
[54]	valid_0's l1: 1.63427e+06
[55]	valid_0's l1: 1.63703e+06
[56]	valid_0's l1: 1.63911e+06
[57]	valid_0's l1: 1.6396e+06
[58]	valid_0's l1: 1.63766e+06
[59]	valid_0's l1: 1.64045e+06
[60]	valid_0's l1: 1.64282e+06
[61]	valid_0's l1: 1.64267e+06
[62]	valid_0's l1: 1.64467e+06
[63]	valid_0's l1: 1.64473e+06
[64]	valid_0's l1: 1.64545e+06
[65]	valid_0's l1: 1.64774e+06
[66]	valid_0's l1: 1.64728e+06
[67]	valid_0's l1: 1.64694e+06
Early stopping, best iteration is:
[37]	valid_0's l1: 1.61791e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.82314e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.53885e+06
[3]	valid_0's l1: 3.28346e+06
[4]	valid_0's l1: 3.05156e+06
[5]	valid_0's l1: 2.85542e+06
[6]	valid_0's l1: 2.75925e+06
[7]	valid_0's l1: 2.66959e+06
[8]	valid_0's l1: 2.52656e+06
[9]	valid_0's l1: 2.40248e+06
[10]	valid_0's l1: 2.29316e+06
[11]	valid_0's l1: 2.1974e+06
[12]	valid_0's l1: 2.15027e+06
[13]	valid_0's l1: 2.07389e+06
[14]	valid_0's l1: 2.04006e+06
[15]	valid_0's l1: 1.98279e+06
[16]	valid_0's l1: 1.93007e+06
[17]	valid_0's l1: 1.88619e+06
[18]	valid_0's l1: 1.84794e+06
[19]	valid_0's l1: 1.8186e+06
[20]	valid_0's l1: 1.78666e+06
[21]	valid_0's l1: 1.76808e+06
[22]	valid_0's l1: 1.75232e+06
[23]	valid_0's l1: 1.73378e+06
[24]	valid_0's l1: 1.71863e+06
[25]	valid_0's l1: 1.70628e+06
[26]	valid_0's l1: 1.69601e+06
[27]	valid_0's l1: 1.68197e+06
[28]	valid_0's l1: 1.67391e+06
[29]	valid_0's l1: 1.66586e+06
[30]	valid_0's l1: 1.66154e+06
[31]	valid_0's l1: 1.65638e+06
[32]	valid_0's l1: 1.65255e+06
[33]	valid_0's l1: 1.65111e+06
[34]	valid_0's l1: 1.65118e+06
[35]	valid_0's l1: 1.64782e+06
[36]	valid_0's l1: 1.64348e+06
[37]	valid_0's l1: 1.64234e+06
[38]	valid_0's l1: 1.6437e+06
[39]	valid_0's l1: 1.64265e+06
[40]	valid_0's l1: 1.64379e+06
[41]	valid_0's l1: 1.64313e+06
[42]	valid_0's l1: 1.6418e+06
[43]	valid_0's l1: 1.64361e+06
[44]	valid_0's l1: 1.64218e+06
[45]	valid_0's l1: 1.64402e+06
[46]	valid_0's l1: 1.64146e+06
[47]	valid_0's l1: 1.64262e+06
[48]	valid_0's l1: 1.64187e+06
[49]	valid_0's l1: 1.64002e+06
[50]	valid_0's l1: 1.63854e+06
[51]	valid_0's l1: 1.63858e+06
[52]	valid_0's l1: 1.63825e+06
[53]	valid_0's l1: 1.64072e+06
[54]	valid_0's l1: 1.64255e+06
[55]	valid_0's l1: 1.64161e+06
[56]	valid_0's l1: 1.64266e+06
[57]	valid_0's l1: 1.64504e+06
[58]	valid_0's l1: 1.64487e+06
[59]	valid_0's l1: 1.64461e+06
[60]	valid_0's l1: 1.6457e+06
[61]	valid_0's l1: 1.64668e+06
[62]	valid_0's l1: 1.64771e+06
[63]	valid_0's l1: 1.64831e+06
[64]	valid_0's l1: 1.64711e+06
[65]	valid_0's l1: 1.64739e+06
[66]	valid_0's l1: 1.6483e+06
[67]	valid_0's l1: 1.64816e+06
[68]	valid_0's l1: 1.64978e+06
[69]	valid_0's l1: 1.65005e+06
[70]	valid_0's l1: 1.65012e+06
[71]	valid_0's l1: 1.65122e+06
[72]	valid_0's l1: 1.6506e+06
[73]	valid_0's l1: 1.6509e+06
[74]	valid_0's l1: 1.6501e+06
[75]	valid_0's l1: 1.65227e+06
[76]	valid_0's l1: 1.65293e+06
[77]	valid_0's l1: 1.65491e+06
[78]	valid_0's l1: 1.65499e+06
[79]	valid_0's l1: 1.65567e+06
[80]	valid_0's l1: 1.65697e+06
[81]	valid_0's l1: 1.65648e+06
[82]	valid_0's l1: 1.65633e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.63825e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90347e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.60447e+06
[3]	valid_0's l1: 3.33163e+06
[4]	valid_0's l1: 3.09336e+06
[5]	valid_0's l1: 2.88614e+06
[6]	valid_0's l1: 2.77812e+06
[7]	valid_0's l1: 2.68595e+06
[8]	valid_0's l1: 2.53776e+06
[9]	valid_0's l1: 2.40858e+06
[10]	valid_0's l1: 2.29804e+06
[11]	valid_0's l1: 2.20018e+06
[12]	valid_0's l1: 2.14893e+06
[13]	valid_0's l1: 2.07158e+06
[14]	valid_0's l1: 2.03795e+06
[15]	valid_0's l1: 1.98575e+06
[16]	valid_0's l1: 1.93925e+06
[17]	valid_0's l1: 1.89833e+06
[18]	valid_0's l1: 1.85799e+06
[19]	valid_0's l1: 1.81604e+06
[20]	valid_0's l1: 1.78718e+06
[21]	valid_0's l1: 1.76339e+06
[22]	valid_0's l1: 1.73882e+06
[23]	valid_0's l1: 1.71904e+06
[24]	valid_0's l1: 1.70315e+06
[25]	valid_0's l1: 1.68543e+06
[26]	valid_0's l1: 1.67107e+06
[27]	valid_0's l1: 1.66136e+06
[28]	valid_0's l1: 1.65118e+06
[29]	valid_0's l1: 1.64208e+06
[30]	valid_0's l1: 1.63366e+06
[31]	valid_0's l1: 1.63059e+06
[32]	valid_0's l1: 1.62535e+06
[33]	valid_0's l1: 1.62527e+06
[34]	valid_0's l1: 1.62184e+06
[35]	valid_0's l1: 1.62203e+06
[36]	valid_0's l1: 1.62009e+06
[37]	valid_0's l1: 1.61825e+06
[38]	valid_0's l1: 1.61759e+06
[39]	valid_0's l1: 1.61438e+06
[40]	valid_0's l1: 1.61596e+06
[41]	valid_0's l1: 1.61631e+06
[42]	valid_0's l1: 1.61543e+06
[43]	valid_0's l1: 1.61522e+06
[44]	valid_0's l1: 1.61456e+06
[45]	valid_0's l1: 1.61175e+06
[46]	valid_0's l1: 1.61233e+06
[47]	valid_0's l1: 1.61393e+06
[48]	valid_0's l1: 1.61366e+06
[49]	valid_0's l1: 1.61534e+06
[50]	valid_0's l1: 1.61645e+06
[51]	valid_0's l1: 1.61485e+06
[52]	valid_0's l1: 1.61601e+06
[53]	valid_0's l1: 1.61818e+06
[54]	valid_0's l1: 1.61939e+06
[55]	valid_0's l1: 1.61976e+06
[56]	valid_0's l1: 1.61974e+06
[57]	valid_0's l1: 1.62078e+06
[58]	valid_0's l1: 1.62052e+06
[59]	valid_0's l1: 1.62096e+06
[60]	valid_0's l1: 1.61909e+06
[61]	valid_0's l1: 1.62111e+06
[62]	valid_0's l1: 1.62204e+06
[63]	valid_0's l1: 1.624e+06
[64]	valid_0's l1: 1.62425e+06
[65]	valid_0's l1: 1.62319e+06
[66]	valid_0's l1: 1.6254e+06
[67]	valid_0's l1: 1.62587e+06
[68]	valid_0's l1: 1.6266e+06
[69]	valid_0's l1: 1.62549e+06
[70]	valid_0's l1: 1.62726e+06
[71]	valid_0's l1: 1.62715e+06
[72]	valid_0's l1: 1.62843e+06
[73]	valid_0's l1: 1.631e+06
[74]	valid_0's l1: 1.62983e+06
[75]	valid_0's l1: 1.63112e+06
Early stopping, best iteration is:
[45]	valid_0's l1: 1.61175e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.8804e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58147e+06
[3]	valid_0's l1: 3.31561e+06
[4]	valid_0's l1: 3.08939e+06
[5]	valid_0's l1: 2.89077e+06
[6]	valid_0's l1: 2.79162e+06
[7]	valid_0's l1: 2.70318e+06
[8]	valid_0's l1: 2.55683e+06
[9]	valid_0's l1: 2.42573e+06
[10]	valid_0's l1: 2.31887e+06
[11]	valid_0's l1: 2.22359e+06
[12]	valid_0's l1: 2.18024e+06
[13]	valid_0's l1: 2.09433e+06
[14]	valid_0's l1: 2.06667e+06
[15]	valid_0's l1: 2.0008e+06
[16]	valid_0's l1: 1.94363e+06
[17]	valid_0's l1: 1.89901e+06
[18]	valid_0's l1: 1.85718e+06
[19]	valid_0's l1: 1.81714e+06
[20]	valid_0's l1: 1.78493e+06
[21]	valid_0's l1: 1.75613e+06
[22]	valid_0's l1: 1.73142e+06
[23]	valid_0's l1: 1.71209e+06
[24]	valid_0's l1: 1.69322e+06
[25]	valid_0's l1: 1.67855e+06
[26]	valid_0's l1: 1.66736e+06
[27]	valid_0's l1: 1.66042e+06
[28]	valid_0's l1: 1.64903e+06
[29]	valid_0's l1: 1.64043e+06
[30]	valid_0's l1: 1.63364e+06
[31]	valid_0's l1: 1.62925e+06
[32]	valid_0's l1: 1.62312e+06
[33]	valid_0's l1: 1.62148e+06
[34]	valid_0's l1: 1.6214e+06
[35]	valid_0's l1: 1.61554e+06
[36]	valid_0's l1: 1.61147e+06
[37]	valid_0's l1: 1.61104e+06
[38]	valid_0's l1: 1.60897e+06
[39]	valid_0's l1: 1.61109e+06
[40]	valid_0's l1: 1.60755e+06
[41]	valid_0's l1: 1.60865e+06
[42]	valid_0's l1: 1.61138e+06
[43]	valid_0's l1: 1.61081e+06
[44]	valid_0's l1: 1.61109e+06
[45]	valid_0's l1: 1.61105e+06
[46]	valid_0's l1: 1.6129e+06
[47]	valid_0's l1: 1.61142e+06
[48]	valid_0's l1: 1.61223e+06
[49]	valid_0's l1: 1.61085e+06
[50]	valid_0's l1: 1.6142e+06
[51]	valid_0's l1: 1.61623e+06
[52]	valid_0's l1: 1.61796e+06
[53]	valid_0's l1: 1.6188e+06
[54]	valid_0's l1: 1.62176e+06
[55]	valid_0's l1: 1.62242e+06
[56]	valid_0's l1: 1.62088e+06
[57]	valid_0's l1: 1.62222e+06
[58]	valid_0's l1: 1.62347e+06
[59]	valid_0's l1: 1.62433e+06
[60]	valid_0's l1: 1.62428e+06
[61]	valid_0's l1: 1.6274e+06
[62]	valid_0's l1: 1.62864e+06
[63]	valid_0's l1: 1.62993e+06
[64]	valid_0's l1: 1.62965e+06
[65]	valid_0's l1: 1.63218e+06
[66]	valid_0's l1: 1.63269e+06
[67]	valid_0's l1: 1.63347e+06
[68]	valid_0's l1: 1.63408e+06
[69]	valid_0's l1: 1.63432e+06
[70]	valid_0's l1: 1.63412e+06
Early stopping, best iteration is:
[40]	valid_0's l1: 1.60755e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.82234e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.53738e+06
[3]	valid_0's l1: 3.28278e+06
[4]	valid_0's l1: 3.05055e+06
[5]	valid_0's l1: 2.85395e+06
[6]	valid_0's l1: 2.76027e+06
[7]	valid_0's l1: 2.67207e+06
[8]	valid_0's l1: 2.52479e+06
[9]	valid_0's l1: 2.39693e+06
[10]	valid_0's l1: 2.2844e+06
[11]	valid_0's l1: 2.18771e+06
[12]	valid_0's l1: 2.13956e+06
[13]	valid_0's l1: 2.06551e+06
[14]	valid_0's l1: 2.03037e+06
[15]	valid_0's l1: 1.97266e+06
[16]	valid_0's l1: 1.92277e+06
[17]	valid_0's l1: 1.88071e+06
[18]	valid_0's l1: 1.84012e+06
[19]	valid_0's l1: 1.80914e+06
[20]	valid_0's l1: 1.78341e+06
[21]	valid_0's l1: 1.75977e+06
[22]	valid_0's l1: 1.73938e+06
[23]	valid_0's l1: 1.71884e+06
[24]	valid_0's l1: 1.704e+06
[25]	valid_0's l1: 1.68982e+06
[26]	valid_0's l1: 1.67853e+06
[27]	valid_0's l1: 1.66707e+06
[28]	valid_0's l1: 1.6575e+06
[29]	valid_0's l1: 1.64879e+06
[30]	valid_0's l1: 1.64292e+06
[31]	valid_0's l1: 1.63945e+06
[32]	valid_0's l1: 1.6373e+06
[33]	valid_0's l1: 1.63527e+06
[34]	valid_0's l1: 1.63174e+06
[35]	valid_0's l1: 1.6321e+06
[36]	valid_0's l1: 1.62921e+06
[37]	valid_0's l1: 1.63137e+06
[38]	valid_0's l1: 1.62857e+06
[39]	valid_0's l1: 1.62869e+06
[40]	valid_0's l1: 1.62636e+06
[41]	valid_0's l1: 1.62635e+06
[42]	valid_0's l1: 1.62345e+06
[43]	valid_0's l1: 1.62422e+06
[44]	valid_0's l1: 1.62453e+06
[45]	valid_0's l1: 1.62611e+06
[46]	valid_0's l1: 1.6248e+06
[47]	valid_0's l1: 1.62704e+06
[48]	valid_0's l1: 1.62781e+06
[49]	valid_0's l1: 1.6272e+06
[50]	valid_0's l1: 1.62614e+06
[51]	valid_0's l1: 1.62683e+06
[52]	valid_0's l1: 1.62589e+06
[53]	valid_0's l1: 1.62841e+06
[54]	valid_0's l1: 1.62995e+06
[55]	valid_0's l1: 1.63114e+06
[56]	valid_0's l1: 1.63104e+06
[57]	valid_0's l1: 1.63222e+06
[58]	valid_0's l1: 1.63222e+06
[59]	valid_0's l1: 1.63304e+06
[60]	valid_0's l1: 1.63325e+06
[61]	valid_0's l1: 1.63288e+06
[62]	valid_0's l1: 1.63368e+06
[63]	valid_0's l1: 1.634e+06
[64]	valid_0's l1: 1.63577e+06
[65]	valid_0's l1: 1.63388e+06
[66]	valid_0's l1: 1.63492e+06
[67]	valid_0's l1: 1.63456e+06
[68]	valid_0's l1: 1.63418e+06
[69]	valid_0's l1: 1.63338e+06
[70]	valid_0's l1: 1.6334e+06
[71]	valid_0's l1: 1.63182e+06
[72]	valid_0's l1: 1.63426e+06
Early stopping, best iteration is:
[42]	valid_0's l1: 1.62345e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90331e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.60346e+06
[3]	valid_0's l1: 3.33147e+06
[4]	valid_0's l1: 3.0943e+06
[5]	valid_0's l1: 2.88691e+06
[6]	valid_0's l1: 2.77737e+06
[7]	valid_0's l1: 2.68585e+06
[8]	valid_0's l1: 2.53803e+06
[9]	valid_0's l1: 2.4083e+06
[10]	valid_0's l1: 2.29773e+06
[11]	valid_0's l1: 2.19713e+06
[12]	valid_0's l1: 2.14466e+06
[13]	valid_0's l1: 2.06369e+06
[14]	valid_0's l1: 2.03015e+06
[15]	valid_0's l1: 1.97551e+06
[16]	valid_0's l1: 1.92629e+06
[17]	valid_0's l1: 1.88563e+06
[18]	valid_0's l1: 1.84773e+06
[19]	valid_0's l1: 1.81126e+06
[20]	valid_0's l1: 1.7812e+06
[21]	valid_0's l1: 1.75382e+06
[22]	valid_0's l1: 1.73287e+06
[23]	valid_0's l1: 1.71452e+06
[24]	valid_0's l1: 1.69565e+06
[25]	valid_0's l1: 1.68183e+06
[26]	valid_0's l1: 1.667e+06
[27]	valid_0's l1: 1.6531e+06
[28]	valid_0's l1: 1.64525e+06
[29]	valid_0's l1: 1.63498e+06
[30]	valid_0's l1: 1.62945e+06
[31]	valid_0's l1: 1.62718e+06
[32]	valid_0's l1: 1.61879e+06
[33]	valid_0's l1: 1.61602e+06
[34]	valid_0's l1: 1.6127e+06
[35]	valid_0's l1: 1.60762e+06
[36]	valid_0's l1: 1.60376e+06
[37]	valid_0's l1: 1.60473e+06
[38]	valid_0's l1: 1.60411e+06
[39]	valid_0's l1: 1.6067e+06
[40]	valid_0's l1: 1.60682e+06
[41]	valid_0's l1: 1.60711e+06
[42]	valid_0's l1: 1.60511e+06
[43]	valid_0's l1: 1.60621e+06
[44]	valid_0's l1: 1.60682e+06
[45]	valid_0's l1: 1.60734e+06
[46]	valid_0's l1: 1.60853e+06
[47]	valid_0's l1: 1.61095e+06
[48]	valid_0's l1: 1.61156e+06
[49]	valid_0's l1: 1.61278e+06
[50]	valid_0's l1: 1.61521e+06
[51]	valid_0's l1: 1.61715e+06
[52]	valid_0's l1: 1.61574e+06
[53]	valid_0's l1: 1.61809e+06
[54]	valid_0's l1: 1.61949e+06
[55]	valid_0's l1: 1.61926e+06
[56]	valid_0's l1: 1.61998e+06
[57]	valid_0's l1: 1.62428e+06
[58]	valid_0's l1: 1.62571e+06
[59]	valid_0's l1: 1.62745e+06
[60]	valid_0's l1: 1.6269e+06
[61]	valid_0's l1: 1.62842e+06
[62]	valid_0's l1: 1.62883e+06
[63]	valid_0's l1: 1.62782e+06
[64]	valid_0's l1: 1.62625e+06
[65]	valid_0's l1: 1.62601e+06
[66]	valid_0's l1: 1.6253e+06
Early stopping, best iteration is:
[36]	valid_0's l1: 1.60376e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.88063e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58111e+06
[3]	valid_0's l1: 3.31471e+06
[4]	valid_0's l1: 3.08971e+06
[5]	valid_0's l1: 2.89137e+06
[6]	valid_0's l1: 2.79091e+06
[7]	valid_0's l1: 2.7016e+06
[8]	valid_0's l1: 2.5545e+06
[9]	valid_0's l1: 2.42672e+06
[10]	valid_0's l1: 2.31773e+06
[11]	valid_0's l1: 2.22329e+06
[12]	valid_0's l1: 2.17855e+06
[13]	valid_0's l1: 2.09992e+06
[14]	valid_0's l1: 2.07693e+06
[15]	valid_0's l1: 2.00991e+06
[16]	valid_0's l1: 1.95164e+06
[17]	valid_0's l1: 1.90423e+06
[18]	valid_0's l1: 1.86449e+06
[19]	valid_0's l1: 1.82493e+06
[20]	valid_0's l1: 1.79157e+06
[21]	valid_0's l1: 1.75899e+06
[22]	valid_0's l1: 1.7361e+06
[23]	valid_0's l1: 1.71289e+06
[24]	valid_0's l1: 1.69566e+06
[25]	valid_0's l1: 1.68045e+06
[26]	valid_0's l1: 1.66649e+06
[27]	valid_0's l1: 1.65602e+06
[28]	valid_0's l1: 1.65022e+06
[29]	valid_0's l1: 1.64358e+06
[30]	valid_0's l1: 1.63472e+06
[31]	valid_0's l1: 1.63274e+06
[32]	valid_0's l1: 1.62521e+06
[33]	valid_0's l1: 1.6268e+06
[34]	valid_0's l1: 1.62937e+06
[35]	valid_0's l1: 1.62197e+06
[36]	valid_0's l1: 1.62251e+06
[37]	valid_0's l1: 1.61791e+06
[38]	valid_0's l1: 1.6191e+06
[39]	valid_0's l1: 1.62166e+06
[40]	valid_0's l1: 1.61971e+06
[41]	valid_0's l1: 1.62036e+06
[42]	valid_0's l1: 1.62022e+06
[43]	valid_0's l1: 1.62122e+06
[44]	valid_0's l1: 1.62306e+06
[45]	valid_0's l1: 1.62404e+06
[46]	valid_0's l1: 1.62464e+06
[47]	valid_0's l1: 1.62581e+06
[48]	valid_0's l1: 1.6233e+06
[49]	valid_0's l1: 1.62433e+06
[50]	valid_0's l1: 1.62647e+06
[51]	valid_0's l1: 1.62283e+06
[52]	valid_0's l1: 1.62738e+06
[53]	valid_0's l1: 1.62974e+06
[54]	valid_0's l1: 1.63427e+06
[55]	valid_0's l1: 1.63703e+06
[56]	valid_0's l1: 1.63911e+06
[57]	valid_0's l1: 1.6396e+06
[58]	valid_0's l1: 1.63766e+06
[59]	valid_0's l1: 1.64045e+06
[60]	valid_0's l1: 1.64282e+06
[61]	valid_0's l1: 1.64267e+06
[62]	valid_0's l1: 1.64467e+06
[63]	valid_0's l1: 1.64473e+06
[64]	valid_0's l1: 1.64545e+06
[65]	valid_0's l1: 1.64774e+06
[66]	valid_0's l1: 1.64728e+06
[67]	valid_0's l1: 1.64694e+06
Early stopping, best iteration is:
[37]	valid_0's l1: 1.61791e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.82314e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.53885e+06
[3]	valid_0's l1: 3.28346e+06
[4]	valid_0's l1: 3.05156e+06
[5]	valid_0's l1: 2.85542e+06
[6]	valid_0's l1: 2.75925e+06
[7]	valid_0's l1: 2.66959e+06
[8]	valid_0's l1: 2.52656e+06
[9]	valid_0's l1: 2.40248e+06
[10]	valid_0's l1: 2.29316e+06
[11]	valid_0's l1: 2.1974e+06
[12]	valid_0's l1: 2.15027e+06
[13]	valid_0's l1: 2.07389e+06
[14]	valid_0's l1: 2.04006e+06
[15]	valid_0's l1: 1.98279e+06
[16]	valid_0's l1: 1.93007e+06
[17]	valid_0's l1: 1.88619e+06
[18]	valid_0's l1: 1.84794e+06
[19]	valid_0's l1: 1.8186e+06
[20]	valid_0's l1: 1.78666e+06
[21]	valid_0's l1: 1.76808e+06
[22]	valid_0's l1: 1.75232e+06
[23]	valid_0's l1: 1.73378e+06
[24]	valid_0's l1: 1.71863e+06
[25]	valid_0's l1: 1.70628e+06
[26]	valid_0's l1: 1.69601e+06
[27]	valid_0's l1: 1.68197e+06
[28]	valid_0's l1: 1.67391e+06
[29]	valid_0's l1: 1.66586e+06
[30]	valid_0's l1: 1.66154e+06
[31]	valid_0's l1: 1.65638e+06
[32]	valid_0's l1: 1.65255e+06
[33]	valid_0's l1: 1.65111e+06
[34]	valid_0's l1: 1.65118e+06
[35]	valid_0's l1: 1.64782e+06
[36]	valid_0's l1: 1.64348e+06
[37]	valid_0's l1: 1.64234e+06
[38]	valid_0's l1: 1.6437e+06
[39]	valid_0's l1: 1.64265e+06
[40]	valid_0's l1: 1.64379e+06
[41]	valid_0's l1: 1.64313e+06
[42]	valid_0's l1: 1.6418e+06
[43]	valid_0's l1: 1.64361e+06
[44]	valid_0's l1: 1.64218e+06
[45]	valid_0's l1: 1.64402e+06
[46]	valid_0's l1: 1.64146e+06
[47]	valid_0's l1: 1.64262e+06
[48]	valid_0's l1: 1.64187e+06
[49]	valid_0's l1: 1.64002e+06
[50]	valid_0's l1: 1.63854e+06
[51]	valid_0's l1: 1.63858e+06
[52]	valid_0's l1: 1.63825e+06
[53]	valid_0's l1: 1.64072e+06
[54]	valid_0's l1: 1.64255e+06
[55]	valid_0's l1: 1.64161e+06
[56]	valid_0's l1: 1.64266e+06
[57]	valid_0's l1: 1.64504e+06
[58]	valid_0's l1: 1.64487e+06
[59]	valid_0's l1: 1.64461e+06
[60]	valid_0's l1: 1.6457e+06
[61]	valid_0's l1: 1.64668e+06
[62]	valid_0's l1: 1.64771e+06
[63]	valid_0's l1: 1.64831e+06
[64]	valid_0's l1: 1.64711e+06
[65]	valid_0's l1: 1.64739e+06
[66]	valid_0's l1: 1.6483e+06
[67]	valid_0's l1: 1.64816e+06
[68]	valid_0's l1: 1.64978e+06
[69]	valid_0's l1: 1.65005e+06
[70]	valid_0's l1: 1.65012e+06
[71]	valid_0's l1: 1.65122e+06
[72]	valid_0's l1: 1.6506e+06
[73]	valid_0's l1: 1.6509e+06
[74]	valid_0's l1: 1.6501e+06
[75]	valid_0's l1: 1.65227e+06
[76]	valid_0's l1: 1.65293e+06
[77]	valid_0's l1: 1.65491e+06
[78]	valid_0's l1: 1.65499e+06
[79]	valid_0's l1: 1.65567e+06
[80]	valid_0's l1: 1.65697e+06
[81]	valid_0's l1: 1.65648e+06
[82]	valid_0's l1: 1.65633e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.63825e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90347e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.60447e+06
[3]	valid_0's l1: 3.33163e+06
[4]	valid_0's l1: 3.09336e+06
[5]	valid_0's l1: 2.88614e+06
[6]	valid_0's l1: 2.77812e+06
[7]	valid_0's l1: 2.68595e+06
[8]	valid_0's l1: 2.53776e+06
[9]	valid_0's l1: 2.40858e+06
[10]	valid_0's l1: 2.29804e+06
[11]	valid_0's l1: 2.20018e+06
[12]	valid_0's l1: 2.14893e+06
[13]	valid_0's l1: 2.07158e+06
[14]	valid_0's l1: 2.03795e+06
[15]	valid_0's l1: 1.98575e+06
[16]	valid_0's l1: 1.93925e+06
[17]	valid_0's l1: 1.89833e+06
[18]	valid_0's l1: 1.85799e+06
[19]	valid_0's l1: 1.81604e+06
[20]	valid_0's l1: 1.78718e+06
[21]	valid_0's l1: 1.76339e+06
[22]	valid_0's l1: 1.73882e+06
[23]	valid_0's l1: 1.71904e+06
[24]	valid_0's l1: 1.70315e+06
[25]	valid_0's l1: 1.68543e+06
[26]	valid_0's l1: 1.67107e+06
[27]	valid_0's l1: 1.66136e+06
[28]	valid_0's l1: 1.65118e+06
[29]	valid_0's l1: 1.64208e+06
[30]	valid_0's l1: 1.63366e+06
[31]	valid_0's l1: 1.63059e+06
[32]	valid_0's l1: 1.62535e+06
[33]	valid_0's l1: 1.62527e+06
[34]	valid_0's l1: 1.62184e+06
[35]	valid_0's l1: 1.62203e+06
[36]	valid_0's l1: 1.62009e+06
[37]	valid_0's l1: 1.61825e+06
[38]	valid_0's l1: 1.61759e+06
[39]	valid_0's l1: 1.61438e+06
[40]	valid_0's l1: 1.61596e+06
[41]	valid_0's l1: 1.61631e+06
[42]	valid_0's l1: 1.61543e+06
[43]	valid_0's l1: 1.61522e+06
[44]	valid_0's l1: 1.61456e+06
[45]	valid_0's l1: 1.61175e+06
[46]	valid_0's l1: 1.61233e+06
[47]	valid_0's l1: 1.61393e+06
[48]	valid_0's l1: 1.61366e+06
[49]	valid_0's l1: 1.61534e+06
[50]	valid_0's l1: 1.61645e+06
[51]	valid_0's l1: 1.61485e+06
[52]	valid_0's l1: 1.61601e+06
[53]	valid_0's l1: 1.61818e+06
[54]	valid_0's l1: 1.61939e+06
[55]	valid_0's l1: 1.61976e+06
[56]	valid_0's l1: 1.61974e+06
[57]	valid_0's l1: 1.62078e+06
[58]	valid_0's l1: 1.62052e+06
[59]	valid_0's l1: 1.62096e+06
[60]	valid_0's l1: 1.61909e+06
[61]	valid_0's l1: 1.62111e+06
[62]	valid_0's l1: 1.62204e+06
[63]	valid_0's l1: 1.624e+06
[64]	valid_0's l1: 1.62425e+06
[65]	valid_0's l1: 1.62319e+06
[66]	valid_0's l1: 1.6254e+06
[67]	valid_0's l1: 1.62587e+06
[68]	valid_0's l1: 1.6266e+06
[69]	valid_0's l1: 1.62549e+06
[70]	valid_0's l1: 1.62726e+06
[71]	valid_0's l1: 1.62715e+06
[72]	valid_0's l1: 1.62843e+06
[73]	valid_0's l1: 1.631e+06
[74]	valid_0's l1: 1.62983e+06
[75]	valid_0's l1: 1.63112e+06
Early stopping, best iteration is:
[45]	valid_0's l1: 1.61175e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90081e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.59582e+06
[3]	valid_0's l1: 3.33132e+06
[4]	valid_0's l1: 3.098e+06
[5]	valid_0's l1: 2.89114e+06
[6]	valid_0's l1: 2.80556e+06
[7]	valid_0's l1: 2.72592e+06
[8]	valid_0's l1: 2.58085e+06
[9]	valid_0's l1: 2.45021e+06
[10]	valid_0's l1: 2.33527e+06
[11]	valid_0's l1: 2.2391e+06
[12]	valid_0's l1: 2.19693e+06
[13]	valid_0's l1: 2.11329e+06
[14]	valid_0's l1: 2.09066e+06
[15]	valid_0's l1: 2.0198e+06
[16]	valid_0's l1: 1.95972e+06
[17]	valid_0's l1: 1.90723e+06
[18]	valid_0's l1: 1.86494e+06
[19]	valid_0's l1: 1.82292e+06
[20]	valid_0's l1: 1.78873e+06
[21]	valid_0's l1: 1.75883e+06
[22]	valid_0's l1: 1.73505e+06
[23]	valid_0's l1: 1.71207e+06
[24]	valid_0's l1: 1.6975e+06
[25]	valid_0's l1: 1.67955e+06
[26]	valid_0's l1: 1.66097e+06
[27]	valid_0's l1: 1.64628e+06
[28]	valid_0's l1: 1.63646e+06
[29]	valid_0's l1: 1.62795e+06
[30]	valid_0's l1: 1.61504e+06
[31]	valid_0's l1: 1.61319e+06
[32]	valid_0's l1: 1.60404e+06
[33]	valid_0's l1: 1.59766e+06
[34]	valid_0's l1: 1.59666e+06
[35]	valid_0's l1: 1.59503e+06
[36]	valid_0's l1: 1.5944e+06
[37]	valid_0's l1: 1.59336e+06
[38]	valid_0's l1: 1.59277e+06
[39]	valid_0's l1: 1.58696e+06
[40]	valid_0's l1: 1.58668e+06
[41]	valid_0's l1: 1.58367e+06
[42]	valid_0's l1: 1.58363e+06
[43]	valid_0's l1: 1.58274e+06
[44]	valid_0's l1: 1.57959e+06
[45]	valid_0's l1: 1.58042e+06
[46]	valid_0's l1: 1.58166e+06
[47]	valid_0's l1: 1.57879e+06
[48]	valid_0's l1: 1.57911e+06
[49]	valid_0's l1: 1.58157e+06
[50]	valid_0's l1: 1.58284e+06
[51]	valid_0's l1: 1.58312e+06
[52]	valid_0's l1: 1.57803e+06
[53]	valid_0's l1: 1.57922e+06
[54]	valid_0's l1: 1.58002e+06
[55]	valid_0's l1: 1.58115e+06
[56]	valid_0's l1: 1.58287e+06
[57]	valid_0's l1: 1.58232e+06
[58]	valid_0's l1: 1.58297e+06
[59]	valid_0's l1: 1.58295e+06
[60]	valid_0's l1: 1.58504e+06
[61]	valid_0's l1: 1.58515e+06
[62]	valid_0's l1: 1.58561e+06
[63]	valid_0's l1: 1.58709e+06
[64]	valid_0's l1: 1.58507e+06
[65]	valid_0's l1: 1.58536e+06
[66]	valid_0's l1: 1.58432e+06
[67]	valid_0's l1: 1.58613e+06
[68]	valid_0's l1: 1.58538e+06
[69]	valid_0's l1: 1.58021e+06
[70]	valid_0's l1: 1.5804e+06
[71]	valid_0's l1: 1.58138e+06
[72]	valid_0's l1: 1.58121e+06
[73]	valid_0's l1: 1.58254e+06
[74]	valid_0's l1: 1.58233e+06
[75]	valid_0's l1: 1.58032e+06
[76]	valid_0's l1: 1.58063e+06
[77]	valid_0's l1: 1.58148e+06
[78]	valid_0's l1: 1.57924e+06
[79]	valid_0's l1: 1.58047e+06
[80]	valid_0's l1: 1.58135e+06
[81]	valid_0's l1: 1.57956e+06
[82]	valid_0's l1: 1.57943e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.57803e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.84197e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.55342e+06
[3]	valid_0's l1: 3.29726e+06
[4]	valid_0's l1: 3.06367e+06
[5]	valid_0's l1: 2.86201e+06
[6]	valid_0's l1: 2.77263e+06
[7]	valid_0's l1: 2.69511e+06
[8]	valid_0's l1: 2.54647e+06
[9]	valid_0's l1: 2.41522e+06
[10]	valid_0's l1: 2.30494e+06
[11]	valid_0's l1: 2.20889e+06
[12]	valid_0's l1: 2.16019e+06
[13]	valid_0's l1: 2.08103e+06
[14]	valid_0's l1: 2.05287e+06
[15]	valid_0's l1: 1.98986e+06
[16]	valid_0's l1: 1.93642e+06
[17]	valid_0's l1: 1.89289e+06
[18]	valid_0's l1: 1.8552e+06
[19]	valid_0's l1: 1.82202e+06
[20]	valid_0's l1: 1.79212e+06
[21]	valid_0's l1: 1.76743e+06
[22]	valid_0's l1: 1.74428e+06
[23]	valid_0's l1: 1.72953e+06
[24]	valid_0's l1: 1.71457e+06
[25]	valid_0's l1: 1.70052e+06
[26]	valid_0's l1: 1.68713e+06
[27]	valid_0's l1: 1.67176e+06
[28]	valid_0's l1: 1.6637e+06
[29]	valid_0's l1: 1.6565e+06
[30]	valid_0's l1: 1.64877e+06
[31]	valid_0's l1: 1.63661e+06
[32]	valid_0's l1: 1.62954e+06
[33]	valid_0's l1: 1.62726e+06
[34]	valid_0's l1: 1.61977e+06
[35]	valid_0's l1: 1.61731e+06
[36]	valid_0's l1: 1.60926e+06
[37]	valid_0's l1: 1.60815e+06
[38]	valid_0's l1: 1.60559e+06
[39]	valid_0's l1: 1.60279e+06
[40]	valid_0's l1: 1.6027e+06
[41]	valid_0's l1: 1.59799e+06
[42]	valid_0's l1: 1.59741e+06
[43]	valid_0's l1: 1.59672e+06
[44]	valid_0's l1: 1.5961e+06
[45]	valid_0's l1: 1.59397e+06
[46]	valid_0's l1: 1.59023e+06
[47]	valid_0's l1: 1.58949e+06
[48]	valid_0's l1: 1.58952e+06
[49]	valid_0's l1: 1.58677e+06
[50]	valid_0's l1: 1.58555e+06
[51]	valid_0's l1: 1.58606e+06
[52]	valid_0's l1: 1.58418e+06
[53]	valid_0's l1: 1.58507e+06
[54]	valid_0's l1: 1.58497e+06
[55]	valid_0's l1: 1.58581e+06
[56]	valid_0's l1: 1.58421e+06
[57]	valid_0's l1: 1.58225e+06
[58]	valid_0's l1: 1.5824e+06
[59]	valid_0's l1: 1.58158e+06
[60]	valid_0's l1: 1.58005e+06
[61]	valid_0's l1: 1.58137e+06
[62]	valid_0's l1: 1.58155e+06
[63]	valid_0's l1: 1.58091e+06
[64]	valid_0's l1: 1.58157e+06
[65]	valid_0's l1: 1.58289e+06
[66]	valid_0's l1: 1.58426e+06
[67]	valid_0's l1: 1.5831e+06
[68]	valid_0's l1: 1.58122e+06
[69]	valid_0's l1: 1.58157e+06
[70]	valid_0's l1: 1.58213e+06
[71]	valid_0's l1: 1.58303e+06
[72]	valid_0's l1: 1.58277e+06
[73]	valid_0's l1: 1.58444e+06
[74]	valid_0's l1: 1.58325e+06
[75]	valid_0's l1: 1.58386e+06
[76]	valid_0's l1: 1.58379e+06
[77]	valid_0's l1: 1.58402e+06
[78]	valid_0's l1: 1.58249e+06
[79]	valid_0's l1: 1.58142e+06
[80]	valid_0's l1: 1.58035e+06
[81]	valid_0's l1: 1.5809e+06
[82]	valid_0's l1: 1.57963e+06
[83]	valid_0's l1: 1.58035e+06
[84]	valid_0's l1: 1.57931e+06
[85]	valid_0's l1: 1.58015e+06
[86]	valid_0's l1: 1.57969e+06
[87]	valid_0's l1: 1.57984e+06
[88]	valid_0's l1: 1.58188e+06
[89]	valid_0's l1: 1.58304e+06
[90]	valid_0's l1: 1.58135e+06
[91]	valid_0's l1: 1.58232e+06
[92]	valid_0's l1: 1.58257e+06
[93]	valid_0's l1: 1.58241e+06
[94]	valid_0's l1: 1.58202e+06
[95]	valid_0's l1: 1.5829e+06
[96]	valid_0's l1: 1.58211e+06
[97]	valid_0's l1: 1.58216e+06
[98]	valid_0's l1: 1.58011e+06
[99]	valid_0's l1: 1.58153e+06
[100]	valid_0's l1: 1.58087e+06
[101]	valid_0's l1: 1.58134e+06
[102]	valid_0's l1: 1.58232e+06
[103]	valid_0's l1: 1.58281e+06
[104]	valid_0's l1: 1.58261e+06
[105]	valid_0's l1: 1.58244e+06
[106]	valid_0's l1: 1.58099e+06
[107]	valid_0's l1: 1.58132e+06
[108]	valid_0's l1: 1.58327e+06
[109]	valid_0's l1: 1.58179e+06
[110]	valid_0's l1: 1.58224e+06
[111]	valid_0's l1: 1.58337e+06
[112]	valid_0's l1: 1.58372e+06
[113]	valid_0's l1: 1.58488e+06
[114]	valid_0's l1: 1.58443e+06
Early stopping, best iteration is:
[84]	valid_0's l1: 1.57931e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.92163e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.62051e+06
[3]	valid_0's l1: 3.34817e+06
[4]	valid_0's l1: 3.11253e+06
[5]	valid_0's l1: 2.90409e+06
[6]	valid_0's l1: 2.80635e+06
[7]	valid_0's l1: 2.7208e+06
[8]	valid_0's l1: 2.56756e+06
[9]	valid_0's l1: 2.43616e+06
[10]	valid_0's l1: 2.32151e+06
[11]	valid_0's l1: 2.21898e+06
[12]	valid_0's l1: 2.17242e+06
[13]	valid_0's l1: 2.09115e+06
[14]	valid_0's l1: 2.06811e+06
[15]	valid_0's l1: 2.00714e+06
[16]	valid_0's l1: 1.95139e+06
[17]	valid_0's l1: 1.90248e+06
[18]	valid_0's l1: 1.86218e+06
[19]	valid_0's l1: 1.8302e+06
[20]	valid_0's l1: 1.79563e+06
[21]	valid_0's l1: 1.76865e+06
[22]	valid_0's l1: 1.7457e+06
[23]	valid_0's l1: 1.72433e+06
[24]	valid_0's l1: 1.70488e+06
[25]	valid_0's l1: 1.69042e+06
[26]	valid_0's l1: 1.67479e+06
[27]	valid_0's l1: 1.66188e+06
[28]	valid_0's l1: 1.65166e+06
[29]	valid_0's l1: 1.64814e+06
[30]	valid_0's l1: 1.64016e+06
[31]	valid_0's l1: 1.63678e+06
[32]	valid_0's l1: 1.6258e+06
[33]	valid_0's l1: 1.62234e+06
[34]	valid_0's l1: 1.6162e+06
[35]	valid_0's l1: 1.61559e+06
[36]	valid_0's l1: 1.61593e+06
[37]	valid_0's l1: 1.61618e+06
[38]	valid_0's l1: 1.61257e+06
[39]	valid_0's l1: 1.61192e+06
[40]	valid_0's l1: 1.61066e+06
[41]	valid_0's l1: 1.6056e+06
[42]	valid_0's l1: 1.60543e+06
[43]	valid_0's l1: 1.60025e+06
[44]	valid_0's l1: 1.59933e+06
[45]	valid_0's l1: 1.59983e+06
[46]	valid_0's l1: 1.598e+06
[47]	valid_0's l1: 1.5973e+06
[48]	valid_0's l1: 1.59616e+06
[49]	valid_0's l1: 1.59576e+06
[50]	valid_0's l1: 1.59615e+06
[51]	valid_0's l1: 1.59734e+06
[52]	valid_0's l1: 1.59782e+06
[53]	valid_0's l1: 1.59771e+06
[54]	valid_0's l1: 1.60004e+06
[55]	valid_0's l1: 1.59929e+06
[56]	valid_0's l1: 1.59945e+06
[57]	valid_0's l1: 1.59901e+06
[58]	valid_0's l1: 1.59883e+06
[59]	valid_0's l1: 1.59938e+06
[60]	valid_0's l1: 1.5966e+06
[61]	valid_0's l1: 1.59638e+06
[62]	valid_0's l1: 1.59613e+06
[63]	valid_0's l1: 1.5968e+06
[64]	valid_0's l1: 1.59515e+06
[65]	valid_0's l1: 1.59466e+06
[66]	valid_0's l1: 1.59371e+06
[67]	valid_0's l1: 1.59335e+06
[68]	valid_0's l1: 1.59401e+06
[69]	valid_0's l1: 1.59414e+06
[70]	valid_0's l1: 1.59451e+06
[71]	valid_0's l1: 1.59378e+06
[72]	valid_0's l1: 1.59398e+06
[73]	valid_0's l1: 1.59567e+06
[74]	valid_0's l1: 1.59669e+06
[75]	valid_0's l1: 1.59692e+06
[76]	valid_0's l1: 1.59488e+06
[77]	valid_0's l1: 1.59495e+06
[78]	valid_0's l1: 1.59601e+06
[79]	valid_0's l1: 1.59527e+06
[80]	valid_0's l1: 1.59578e+06
[81]	valid_0's l1: 1.59741e+06
[82]	valid_0's l1: 1.59656e+06
[83]	valid_0's l1: 1.59728e+06
[84]	valid_0's l1: 1.59658e+06
[85]	valid_0's l1: 1.59677e+06
[86]	valid_0's l1: 1.59746e+06
[87]	valid_0's l1: 1.59818e+06
[88]	valid_0's l1: 1.59816e+06
[89]	valid_0's l1: 1.59824e+06
[90]	valid_0's l1: 1.5967e+06
[91]	valid_0's l1: 1.59675e+06
[92]	valid_0's l1: 1.59634e+06
[93]	valid_0's l1: 1.59721e+06
[94]	valid_0's l1: 1.59734e+06
[95]	valid_0's l1: 1.59877e+06
[96]	valid_0's l1: 1.59858e+06
[97]	valid_0's l1: 1.59878e+06
Early stopping, best iteration is:
[67]	valid_0's l1: 1.59335e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90081e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.59582e+06
[3]	valid_0's l1: 3.33132e+06
[4]	valid_0's l1: 3.098e+06
[5]	valid_0's l1: 2.89114e+06
[6]	valid_0's l1: 2.80556e+06
[7]	valid_0's l1: 2.72592e+06
[8]	valid_0's l1: 2.58085e+06
[9]	valid_0's l1: 2.45021e+06
[10]	valid_0's l1: 2.33527e+06
[11]	valid_0's l1: 2.2391e+06
[12]	valid_0's l1: 2.19693e+06
[13]	valid_0's l1: 2.11329e+06
[14]	valid_0's l1: 2.09066e+06
[15]	valid_0's l1: 2.0198e+06
[16]	valid_0's l1: 1.95972e+06
[17]	valid_0's l1: 1.90723e+06
[18]	valid_0's l1: 1.86494e+06
[19]	valid_0's l1: 1.82292e+06
[20]	valid_0's l1: 1.78873e+06
[21]	valid_0's l1: 1.75883e+06
[22]	valid_0's l1: 1.73505e+06
[23]	valid_0's l1: 1.71207e+06
[24]	valid_0's l1: 1.6975e+06
[25]	valid_0's l1: 1.67955e+06
[26]	valid_0's l1: 1.66097e+06
[27]	valid_0's l1: 1.64628e+06
[28]	valid_0's l1: 1.63646e+06
[29]	valid_0's l1: 1.62795e+06
[30]	valid_0's l1: 1.61504e+06
[31]	valid_0's l1: 1.61319e+06
[32]	valid_0's l1: 1.60404e+06
[33]	valid_0's l1: 1.59766e+06
[34]	valid_0's l1: 1.59666e+06
[35]	valid_0's l1: 1.59503e+06
[36]	valid_0's l1: 1.5944e+06
[37]	valid_0's l1: 1.59336e+06
[38]	valid_0's l1: 1.59277e+06
[39]	valid_0's l1: 1.58696e+06
[40]	valid_0's l1: 1.58668e+06
[41]	valid_0's l1: 1.58367e+06
[42]	valid_0's l1: 1.58363e+06
[43]	valid_0's l1: 1.58274e+06
[44]	valid_0's l1: 1.57959e+06
[45]	valid_0's l1: 1.58042e+06
[46]	valid_0's l1: 1.58166e+06
[47]	valid_0's l1: 1.57879e+06
[48]	valid_0's l1: 1.57911e+06
[49]	valid_0's l1: 1.58157e+06
[50]	valid_0's l1: 1.58284e+06
[51]	valid_0's l1: 1.58312e+06
[52]	valid_0's l1: 1.57803e+06
[53]	valid_0's l1: 1.57922e+06
[54]	valid_0's l1: 1.58002e+06
[55]	valid_0's l1: 1.58115e+06
[56]	valid_0's l1: 1.58287e+06
[57]	valid_0's l1: 1.58232e+06
[58]	valid_0's l1: 1.58297e+06
[59]	valid_0's l1: 1.58295e+06
[60]	valid_0's l1: 1.58504e+06
[61]	valid_0's l1: 1.58515e+06
[62]	valid_0's l1: 1.58561e+06
[63]	valid_0's l1: 1.58709e+06
[64]	valid_0's l1: 1.58507e+06
[65]	valid_0's l1: 1.58536e+06
[66]	valid_0's l1: 1.58432e+06
[67]	valid_0's l1: 1.58613e+06
[68]	valid_0's l1: 1.58538e+06
[69]	valid_0's l1: 1.58021e+06
[70]	valid_0's l1: 1.5804e+06
[71]	valid_0's l1: 1.58138e+06
[72]	valid_0's l1: 1.58121e+06
[73]	valid_0's l1: 1.58254e+06
[74]	valid_0's l1: 1.58233e+06
[75]	valid_0's l1: 1.58032e+06
[76]	valid_0's l1: 1.58063e+06
[77]	valid_0's l1: 1.58148e+06
[78]	valid_0's l1: 1.57924e+06
[79]	valid_0's l1: 1.58047e+06
[80]	valid_0's l1: 1.58135e+06
[81]	valid_0's l1: 1.57956e+06
[82]	valid_0's l1: 1.57943e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.57803e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.84197e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.55342e+06
[3]	valid_0's l1: 3.29726e+06
[4]	valid_0's l1: 3.06367e+06
[5]	valid_0's l1: 2.86201e+06
[6]	valid_0's l1: 2.77263e+06
[7]	valid_0's l1: 2.69511e+06
[8]	valid_0's l1: 2.54647e+06
[9]	valid_0's l1: 2.41522e+06
[10]	valid_0's l1: 2.30494e+06
[11]	valid_0's l1: 2.20889e+06
[12]	valid_0's l1: 2.16019e+06
[13]	valid_0's l1: 2.08103e+06
[14]	valid_0's l1: 2.05287e+06
[15]	valid_0's l1: 1.98986e+06
[16]	valid_0's l1: 1.93642e+06
[17]	valid_0's l1: 1.89289e+06
[18]	valid_0's l1: 1.8552e+06
[19]	valid_0's l1: 1.82202e+06
[20]	valid_0's l1: 1.79212e+06
[21]	valid_0's l1: 1.76743e+06
[22]	valid_0's l1: 1.74428e+06
[23]	valid_0's l1: 1.72953e+06
[24]	valid_0's l1: 1.71457e+06
[25]	valid_0's l1: 1.70052e+06
[26]	valid_0's l1: 1.68713e+06
[27]	valid_0's l1: 1.67176e+06
[28]	valid_0's l1: 1.6637e+06
[29]	valid_0's l1: 1.6565e+06
[30]	valid_0's l1: 1.64877e+06
[31]	valid_0's l1: 1.63661e+06
[32]	valid_0's l1: 1.62954e+06
[33]	valid_0's l1: 1.62726e+06
[34]	valid_0's l1: 1.61977e+06
[35]	valid_0's l1: 1.61731e+06
[36]	valid_0's l1: 1.60926e+06
[37]	valid_0's l1: 1.60815e+06
[38]	valid_0's l1: 1.60559e+06
[39]	valid_0's l1: 1.60279e+06
[40]	valid_0's l1: 1.6027e+06
[41]	valid_0's l1: 1.59799e+06
[42]	valid_0's l1: 1.59741e+06
[43]	valid_0's l1: 1.59672e+06
[44]	valid_0's l1: 1.5961e+06
[45]	valid_0's l1: 1.59397e+06
[46]	valid_0's l1: 1.59023e+06
[47]	valid_0's l1: 1.58949e+06
[48]	valid_0's l1: 1.58952e+06
[49]	valid_0's l1: 1.58677e+06
[50]	valid_0's l1: 1.58555e+06
[51]	valid_0's l1: 1.58606e+06
[52]	valid_0's l1: 1.58418e+06
[53]	valid_0's l1: 1.58507e+06
[54]	valid_0's l1: 1.58497e+06
[55]	valid_0's l1: 1.58581e+06
[56]	valid_0's l1: 1.58421e+06
[57]	valid_0's l1: 1.58225e+06
[58]	valid_0's l1: 1.5824e+06
[59]	valid_0's l1: 1.58158e+06
[60]	valid_0's l1: 1.58005e+06
[61]	valid_0's l1: 1.58137e+06
[62]	valid_0's l1: 1.58155e+06
[63]	valid_0's l1: 1.58091e+06
[64]	valid_0's l1: 1.58157e+06
[65]	valid_0's l1: 1.58289e+06
[66]	valid_0's l1: 1.58426e+06
[67]	valid_0's l1: 1.5831e+06
[68]	valid_0's l1: 1.58122e+06
[69]	valid_0's l1: 1.58157e+06
[70]	valid_0's l1: 1.58213e+06
[71]	valid_0's l1: 1.58303e+06
[72]	valid_0's l1: 1.58277e+06
[73]	valid_0's l1: 1.58444e+06
[74]	valid_0's l1: 1.58325e+06
[75]	valid_0's l1: 1.58386e+06
[76]	valid_0's l1: 1.58379e+06
[77]	valid_0's l1: 1.58402e+06
[78]	valid_0's l1: 1.58249e+06
[79]	valid_0's l1: 1.58142e+06
[80]	valid_0's l1: 1.58035e+06
[81]	valid_0's l1: 1.5809e+06
[82]	valid_0's l1: 1.57963e+06
[83]	valid_0's l1: 1.58035e+06
[84]	valid_0's l1: 1.57931e+06
[85]	valid_0's l1: 1.58015e+06
[86]	valid_0's l1: 1.57969e+06
[87]	valid_0's l1: 1.57984e+06
[88]	valid_0's l1: 1.58188e+06
[89]	valid_0's l1: 1.58304e+06
[90]	valid_0's l1: 1.58135e+06
[91]	valid_0's l1: 1.58232e+06
[92]	valid_0's l1: 1.58257e+06
[93]	valid_0's l1: 1.58241e+06
[94]	valid_0's l1: 1.58202e+06
[95]	valid_0's l1: 1.5829e+06
[96]	valid_0's l1: 1.58211e+06
[97]	valid_0's l1: 1.58216e+06
[98]	valid_0's l1: 1.58011e+06
[99]	valid_0's l1: 1.58153e+06
[100]	valid_0's l1: 1.58087e+06
[101]	valid_0's l1: 1.58134e+06
[102]	valid_0's l1: 1.58232e+06
[103]	valid_0's l1: 1.58281e+06
[104]	valid_0's l1: 1.58261e+06
[105]	valid_0's l1: 1.58244e+06
[106]	valid_0's l1: 1.58099e+06
[107]	valid_0's l1: 1.58132e+06
[108]	valid_0's l1: 1.58327e+06
[109]	valid_0's l1: 1.58179e+06
[110]	valid_0's l1: 1.58224e+06
[111]	valid_0's l1: 1.58337e+06
[112]	valid_0's l1: 1.58372e+06
[113]	valid_0's l1: 1.58488e+06
[114]	valid_0's l1: 1.58443e+06
Early stopping, best iteration is:
[84]	valid_0's l1: 1.57931e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.92163e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.62051e+06
[3]	valid_0's l1: 3.34817e+06
[4]	valid_0's l1: 3.11253e+06
[5]	valid_0's l1: 2.90409e+06
[6]	valid_0's l1: 2.80635e+06
[7]	valid_0's l1: 2.7208e+06
[8]	valid_0's l1: 2.56756e+06
[9]	valid_0's l1: 2.43616e+06
[10]	valid_0's l1: 2.32151e+06
[11]	valid_0's l1: 2.21898e+06
[12]	valid_0's l1: 2.17242e+06
[13]	valid_0's l1: 2.09115e+06
[14]	valid_0's l1: 2.06811e+06
[15]	valid_0's l1: 2.00714e+06
[16]	valid_0's l1: 1.95139e+06
[17]	valid_0's l1: 1.90248e+06
[18]	valid_0's l1: 1.86218e+06
[19]	valid_0's l1: 1.8302e+06
[20]	valid_0's l1: 1.79563e+06
[21]	valid_0's l1: 1.76865e+06
[22]	valid_0's l1: 1.7457e+06
[23]	valid_0's l1: 1.72433e+06
[24]	valid_0's l1: 1.70488e+06
[25]	valid_0's l1: 1.69042e+06
[26]	valid_0's l1: 1.67479e+06
[27]	valid_0's l1: 1.66188e+06
[28]	valid_0's l1: 1.65166e+06
[29]	valid_0's l1: 1.64814e+06
[30]	valid_0's l1: 1.64016e+06
[31]	valid_0's l1: 1.63678e+06
[32]	valid_0's l1: 1.6258e+06
[33]	valid_0's l1: 1.62234e+06
[34]	valid_0's l1: 1.6162e+06
[35]	valid_0's l1: 1.61559e+06
[36]	valid_0's l1: 1.61593e+06
[37]	valid_0's l1: 1.61618e+06
[38]	valid_0's l1: 1.61257e+06
[39]	valid_0's l1: 1.61192e+06
[40]	valid_0's l1: 1.61066e+06
[41]	valid_0's l1: 1.6056e+06
[42]	valid_0's l1: 1.60543e+06
[43]	valid_0's l1: 1.60025e+06
[44]	valid_0's l1: 1.59933e+06
[45]	valid_0's l1: 1.59983e+06
[46]	valid_0's l1: 1.598e+06
[47]	valid_0's l1: 1.5973e+06
[48]	valid_0's l1: 1.59616e+06
[49]	valid_0's l1: 1.59576e+06
[50]	valid_0's l1: 1.59615e+06
[51]	valid_0's l1: 1.59734e+06
[52]	valid_0's l1: 1.59782e+06
[53]	valid_0's l1: 1.59771e+06
[54]	valid_0's l1: 1.60004e+06
[55]	valid_0's l1: 1.59929e+06
[56]	valid_0's l1: 1.59945e+06
[57]	valid_0's l1: 1.59901e+06
[58]	valid_0's l1: 1.59883e+06
[59]	valid_0's l1: 1.59938e+06
[60]	valid_0's l1: 1.5966e+06
[61]	valid_0's l1: 1.59638e+06
[62]	valid_0's l1: 1.59613e+06
[63]	valid_0's l1: 1.5968e+06
[64]	valid_0's l1: 1.59515e+06
[65]	valid_0's l1: 1.59466e+06
[66]	valid_0's l1: 1.59371e+06
[67]	valid_0's l1: 1.59335e+06
[68]	valid_0's l1: 1.59401e+06
[69]	valid_0's l1: 1.59414e+06
[70]	valid_0's l1: 1.59451e+06
[71]	valid_0's l1: 1.59378e+06
[72]	valid_0's l1: 1.59398e+06
[73]	valid_0's l1: 1.59567e+06
[74]	valid_0's l1: 1.59669e+06
[75]	valid_0's l1: 1.59692e+06
[76]	valid_0's l1: 1.59488e+06
[77]	valid_0's l1: 1.59495e+06
[78]	valid_0's l1: 1.59601e+06
[79]	valid_0's l1: 1.59527e+06
[80]	valid_0's l1: 1.59578e+06
[81]	valid_0's l1: 1.59741e+06
[82]	valid_0's l1: 1.59656e+06
[83]	valid_0's l1: 1.59728e+06
[84]	valid_0's l1: 1.59658e+06
[85]	valid_0's l1: 1.59677e+06
[86]	valid_0's l1: 1.59746e+06
[87]	valid_0's l1: 1.59818e+06
[88]	valid_0's l1: 1.59816e+06
[89]	valid_0's l1: 1.59824e+06
[90]	valid_0's l1: 1.5967e+06
[91]	valid_0's l1: 1.59675e+06
[92]	valid_0's l1: 1.59634e+06
[93]	valid_0's l1: 1.59721e+06
[94]	valid_0's l1: 1.59734e+06
[95]	valid_0's l1: 1.59877e+06
[96]	valid_0's l1: 1.59858e+06
[97]	valid_0's l1: 1.59878e+06
Early stopping, best iteration is:
[67]	valid_0's l1: 1.59335e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90081e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.59582e+06
[3]	valid_0's l1: 3.33132e+06
[4]	valid_0's l1: 3.098e+06
[5]	valid_0's l1: 2.89114e+06
[6]	valid_0's l1: 2.80556e+06
[7]	valid_0's l1: 2.72592e+06
[8]	valid_0's l1: 2.58085e+06
[9]	valid_0's l1: 2.45021e+06
[10]	valid_0's l1: 2.33527e+06
[11]	valid_0's l1: 2.2391e+06
[12]	valid_0's l1: 2.19693e+06
[13]	valid_0's l1: 2.11329e+06
[14]	valid_0's l1: 2.09066e+06
[15]	valid_0's l1: 2.0198e+06
[16]	valid_0's l1: 1.95972e+06
[17]	valid_0's l1: 1.90723e+06
[18]	valid_0's l1: 1.86494e+06
[19]	valid_0's l1: 1.82292e+06
[20]	valid_0's l1: 1.78873e+06
[21]	valid_0's l1: 1.75883e+06
[22]	valid_0's l1: 1.73505e+06
[23]	valid_0's l1: 1.71207e+06
[24]	valid_0's l1: 1.6975e+06
[25]	valid_0's l1: 1.67955e+06
[26]	valid_0's l1: 1.66097e+06
[27]	valid_0's l1: 1.64628e+06
[28]	valid_0's l1: 1.63646e+06
[29]	valid_0's l1: 1.62795e+06
[30]	valid_0's l1: 1.61504e+06
[31]	valid_0's l1: 1.61319e+06
[32]	valid_0's l1: 1.60404e+06
[33]	valid_0's l1: 1.59766e+06
[34]	valid_0's l1: 1.59666e+06
[35]	valid_0's l1: 1.59503e+06
[36]	valid_0's l1: 1.5944e+06
[37]	valid_0's l1: 1.59336e+06
[38]	valid_0's l1: 1.59277e+06
[39]	valid_0's l1: 1.58696e+06
[40]	valid_0's l1: 1.58668e+06
[41]	valid_0's l1: 1.58367e+06
[42]	valid_0's l1: 1.58363e+06
[43]	valid_0's l1: 1.58274e+06
[44]	valid_0's l1: 1.57959e+06
[45]	valid_0's l1: 1.58042e+06
[46]	valid_0's l1: 1.58166e+06
[47]	valid_0's l1: 1.57879e+06
[48]	valid_0's l1: 1.57911e+06
[49]	valid_0's l1: 1.58157e+06
[50]	valid_0's l1: 1.58284e+06
[51]	valid_0's l1: 1.58312e+06
[52]	valid_0's l1: 1.57803e+06
[53]	valid_0's l1: 1.57922e+06
[54]	valid_0's l1: 1.58002e+06
[55]	valid_0's l1: 1.58115e+06
[56]	valid_0's l1: 1.58287e+06
[57]	valid_0's l1: 1.58232e+06
[58]	valid_0's l1: 1.58297e+06
[59]	valid_0's l1: 1.58295e+06
[60]	valid_0's l1: 1.58504e+06
[61]	valid_0's l1: 1.58515e+06
[62]	valid_0's l1: 1.58561e+06
[63]	valid_0's l1: 1.58709e+06
[64]	valid_0's l1: 1.58507e+06
[65]	valid_0's l1: 1.58536e+06
[66]	valid_0's l1: 1.58432e+06
[67]	valid_0's l1: 1.58613e+06
[68]	valid_0's l1: 1.58538e+06
[69]	valid_0's l1: 1.58021e+06
[70]	valid_0's l1: 1.5804e+06
[71]	valid_0's l1: 1.58138e+06
[72]	valid_0's l1: 1.58121e+06
[73]	valid_0's l1: 1.58254e+06
[74]	valid_0's l1: 1.58233e+06
[75]	valid_0's l1: 1.58032e+06
[76]	valid_0's l1: 1.58063e+06
[77]	valid_0's l1: 1.58148e+06
[78]	valid_0's l1: 1.57924e+06
[79]	valid_0's l1: 1.58047e+06
[80]	valid_0's l1: 1.58135e+06
[81]	valid_0's l1: 1.57956e+06
[82]	valid_0's l1: 1.57943e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.57803e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.84197e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.55342e+06
[3]	valid_0's l1: 3.29726e+06
[4]	valid_0's l1: 3.06367e+06
[5]	valid_0's l1: 2.86201e+06
[6]	valid_0's l1: 2.77263e+06
[7]	valid_0's l1: 2.69511e+06
[8]	valid_0's l1: 2.54647e+06
[9]	valid_0's l1: 2.41522e+06
[10]	valid_0's l1: 2.30494e+06
[11]	valid_0's l1: 2.20889e+06
[12]	valid_0's l1: 2.16019e+06
[13]	valid_0's l1: 2.08103e+06
[14]	valid_0's l1: 2.05287e+06
[15]	valid_0's l1: 1.98986e+06
[16]	valid_0's l1: 1.93642e+06
[17]	valid_0's l1: 1.89289e+06
[18]	valid_0's l1: 1.8552e+06
[19]	valid_0's l1: 1.82202e+06
[20]	valid_0's l1: 1.79212e+06
[21]	valid_0's l1: 1.76743e+06
[22]	valid_0's l1: 1.74428e+06
[23]	valid_0's l1: 1.72953e+06
[24]	valid_0's l1: 1.71457e+06
[25]	valid_0's l1: 1.70052e+06
[26]	valid_0's l1: 1.68713e+06
[27]	valid_0's l1: 1.67176e+06
[28]	valid_0's l1: 1.6637e+06
[29]	valid_0's l1: 1.6565e+06
[30]	valid_0's l1: 1.64877e+06
[31]	valid_0's l1: 1.63661e+06
[32]	valid_0's l1: 1.62954e+06
[33]	valid_0's l1: 1.62726e+06
[34]	valid_0's l1: 1.61977e+06
[35]	valid_0's l1: 1.61731e+06
[36]	valid_0's l1: 1.60926e+06
[37]	valid_0's l1: 1.60815e+06
[38]	valid_0's l1: 1.60559e+06
[39]	valid_0's l1: 1.60279e+06
[40]	valid_0's l1: 1.6027e+06
[41]	valid_0's l1: 1.59799e+06
[42]	valid_0's l1: 1.59741e+06
[43]	valid_0's l1: 1.59672e+06
[44]	valid_0's l1: 1.5961e+06
[45]	valid_0's l1: 1.59397e+06
[46]	valid_0's l1: 1.59023e+06
[47]	valid_0's l1: 1.58949e+06
[48]	valid_0's l1: 1.58952e+06
[49]	valid_0's l1: 1.58677e+06
[50]	valid_0's l1: 1.58555e+06
[51]	valid_0's l1: 1.58606e+06
[52]	valid_0's l1: 1.58418e+06
[53]	valid_0's l1: 1.58507e+06
[54]	valid_0's l1: 1.58497e+06
[55]	valid_0's l1: 1.58581e+06
[56]	valid_0's l1: 1.58421e+06
[57]	valid_0's l1: 1.58225e+06
[58]	valid_0's l1: 1.5824e+06
[59]	valid_0's l1: 1.58158e+06
[60]	valid_0's l1: 1.58005e+06
[61]	valid_0's l1: 1.58137e+06
[62]	valid_0's l1: 1.58155e+06
[63]	valid_0's l1: 1.58091e+06
[64]	valid_0's l1: 1.58157e+06
[65]	valid_0's l1: 1.58289e+06
[66]	valid_0's l1: 1.58426e+06
[67]	valid_0's l1: 1.5831e+06
[68]	valid_0's l1: 1.58122e+06
[69]	valid_0's l1: 1.58157e+06
[70]	valid_0's l1: 1.58213e+06
[71]	valid_0's l1: 1.58303e+06
[72]	valid_0's l1: 1.58277e+06
[73]	valid_0's l1: 1.58444e+06
[74]	valid_0's l1: 1.58325e+06
[75]	valid_0's l1: 1.58386e+06
[76]	valid_0's l1: 1.58379e+06
[77]	valid_0's l1: 1.58402e+06
[78]	valid_0's l1: 1.58249e+06
[79]	valid_0's l1: 1.58142e+06
[80]	valid_0's l1: 1.58035e+06
[81]	valid_0's l1: 1.5809e+06
[82]	valid_0's l1: 1.57963e+06
[83]	valid_0's l1: 1.58035e+06
[84]	valid_0's l1: 1.57931e+06
[85]	valid_0's l1: 1.58015e+06
[86]	valid_0's l1: 1.57969e+06
[87]	valid_0's l1: 1.57984e+06
[88]	valid_0's l1: 1.58188e+06
[89]	valid_0's l1: 1.58304e+06
[90]	valid_0's l1: 1.58135e+06
[91]	valid_0's l1: 1.58232e+06
[92]	valid_0's l1: 1.58257e+06
[93]	valid_0's l1: 1.58241e+06
[94]	valid_0's l1: 1.58202e+06
[95]	valid_0's l1: 1.5829e+06
[96]	valid_0's l1: 1.58211e+06
[97]	valid_0's l1: 1.58216e+06
[98]	valid_0's l1: 1.58011e+06
[99]	valid_0's l1: 1.58153e+06
[100]	valid_0's l1: 1.58087e+06
[101]	valid_0's l1: 1.58134e+06
[102]	valid_0's l1: 1.58232e+06
[103]	valid_0's l1: 1.58281e+06
[104]	valid_0's l1: 1.58261e+06
[105]	valid_0's l1: 1.58244e+06
[106]	valid_0's l1: 1.58099e+06
[107]	valid_0's l1: 1.58132e+06
[108]	valid_0's l1: 1.58327e+06
[109]	valid_0's l1: 1.58179e+06
[110]	valid_0's l1: 1.58224e+06
[111]	valid_0's l1: 1.58337e+06
[112]	valid_0's l1: 1.58372e+06
[113]	valid_0's l1: 1.58488e+06
[114]	valid_0's l1: 1.58443e+06
Early stopping, best iteration is:
[84]	valid_0's l1: 1.57931e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.92163e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.62051e+06
[3]	valid_0's l1: 3.34817e+06
[4]	valid_0's l1: 3.11253e+06
[5]	valid_0's l1: 2.90409e+06
[6]	valid_0's l1: 2.80635e+06
[7]	valid_0's l1: 2.7208e+06
[8]	valid_0's l1: 2.56756e+06
[9]	valid_0's l1: 2.43616e+06
[10]	valid_0's l1: 2.32151e+06
[11]	valid_0's l1: 2.21898e+06
[12]	valid_0's l1: 2.17242e+06
[13]	valid_0's l1: 2.09115e+06
[14]	valid_0's l1: 2.06811e+06
[15]	valid_0's l1: 2.00714e+06
[16]	valid_0's l1: 1.95139e+06
[17]	valid_0's l1: 1.90248e+06
[18]	valid_0's l1: 1.86218e+06
[19]	valid_0's l1: 1.8302e+06
[20]	valid_0's l1: 1.79563e+06
[21]	valid_0's l1: 1.76865e+06
[22]	valid_0's l1: 1.7457e+06
[23]	valid_0's l1: 1.72433e+06
[24]	valid_0's l1: 1.70488e+06
[25]	valid_0's l1: 1.69042e+06
[26]	valid_0's l1: 1.67479e+06
[27]	valid_0's l1: 1.66188e+06
[28]	valid_0's l1: 1.65166e+06
[29]	valid_0's l1: 1.64814e+06
[30]	valid_0's l1: 1.64016e+06
[31]	valid_0's l1: 1.63678e+06
[32]	valid_0's l1: 1.6258e+06
[33]	valid_0's l1: 1.62234e+06
[34]	valid_0's l1: 1.6162e+06
[35]	valid_0's l1: 1.61559e+06
[36]	valid_0's l1: 1.61593e+06
[37]	valid_0's l1: 1.61618e+06
[38]	valid_0's l1: 1.61257e+06
[39]	valid_0's l1: 1.61192e+06
[40]	valid_0's l1: 1.61066e+06
[41]	valid_0's l1: 1.6056e+06
[42]	valid_0's l1: 1.60543e+06
[43]	valid_0's l1: 1.60025e+06
[44]	valid_0's l1: 1.59933e+06
[45]	valid_0's l1: 1.59983e+06
[46]	valid_0's l1: 1.598e+06
[47]	valid_0's l1: 1.5973e+06
[48]	valid_0's l1: 1.59616e+06
[49]	valid_0's l1: 1.59576e+06
[50]	valid_0's l1: 1.59615e+06
[51]	valid_0's l1: 1.59734e+06
[52]	valid_0's l1: 1.59782e+06
[53]	valid_0's l1: 1.59771e+06
[54]	valid_0's l1: 1.60004e+06
[55]	valid_0's l1: 1.59929e+06
[56]	valid_0's l1: 1.59945e+06
[57]	valid_0's l1: 1.59901e+06
[58]	valid_0's l1: 1.59883e+06
[59]	valid_0's l1: 1.59938e+06
[60]	valid_0's l1: 1.5966e+06
[61]	valid_0's l1: 1.59638e+06
[62]	valid_0's l1: 1.59613e+06
[63]	valid_0's l1: 1.5968e+06
[64]	valid_0's l1: 1.59515e+06
[65]	valid_0's l1: 1.59466e+06
[66]	valid_0's l1: 1.59371e+06
[67]	valid_0's l1: 1.59335e+06
[68]	valid_0's l1: 1.59401e+06
[69]	valid_0's l1: 1.59414e+06
[70]	valid_0's l1: 1.59451e+06
[71]	valid_0's l1: 1.59378e+06
[72]	valid_0's l1: 1.59398e+06
[73]	valid_0's l1: 1.59567e+06
[74]	valid_0's l1: 1.59669e+06
[75]	valid_0's l1: 1.59692e+06
[76]	valid_0's l1: 1.59488e+06
[77]	valid_0's l1: 1.59495e+06
[78]	valid_0's l1: 1.59601e+06
[79]	valid_0's l1: 1.59527e+06
[80]	valid_0's l1: 1.59578e+06
[81]	valid_0's l1: 1.59741e+06
[82]	valid_0's l1: 1.59656e+06
[83]	valid_0's l1: 1.59728e+06
[84]	valid_0's l1: 1.59658e+06
[85]	valid_0's l1: 1.59677e+06
[86]	valid_0's l1: 1.59746e+06
[87]	valid_0's l1: 1.59818e+06
[88]	valid_0's l1: 1.59816e+06
[89]	valid_0's l1: 1.59824e+06
[90]	valid_0's l1: 1.5967e+06
[91]	valid_0's l1: 1.59675e+06
[92]	valid_0's l1: 1.59634e+06
[93]	valid_0's l1: 1.59721e+06
[94]	valid_0's l1: 1.59734e+06
[95]	valid_0's l1: 1.59877e+06
[96]	valid_0's l1: 1.59858e+06
[97]	valid_0's l1: 1.59878e+06
Early stopping, best iteration is:
[67]	valid_0's l1: 1.59335e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90081e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.59582e+06
[3]	valid_0's l1: 3.33132e+06
[4]	valid_0's l1: 3.098e+06
[5]	valid_0's l1: 2.89114e+06
[6]	valid_0's l1: 2.80556e+06
[7]	valid_0's l1: 2.72592e+06
[8]	valid_0's l1: 2.58085e+06
[9]	valid_0's l1: 2.45021e+06
[10]	valid_0's l1: 2.33527e+06
[11]	valid_0's l1: 2.2391e+06
[12]	valid_0's l1: 2.19693e+06
[13]	valid_0's l1: 2.11329e+06
[14]	valid_0's l1: 2.09066e+06
[15]	valid_0's l1: 2.0198e+06
[16]	valid_0's l1: 1.95972e+06
[17]	valid_0's l1: 1.90723e+06
[18]	valid_0's l1: 1.86494e+06
[19]	valid_0's l1: 1.82292e+06
[20]	valid_0's l1: 1.78873e+06
[21]	valid_0's l1: 1.75883e+06
[22]	valid_0's l1: 1.73505e+06
[23]	valid_0's l1: 1.71207e+06
[24]	valid_0's l1: 1.6975e+06
[25]	valid_0's l1: 1.67955e+06
[26]	valid_0's l1: 1.66097e+06
[27]	valid_0's l1: 1.64628e+06
[28]	valid_0's l1: 1.63646e+06
[29]	valid_0's l1: 1.62795e+06
[30]	valid_0's l1: 1.61504e+06
[31]	valid_0's l1: 1.61319e+06
[32]	valid_0's l1: 1.60404e+06
[33]	valid_0's l1: 1.59766e+06
[34]	valid_0's l1: 1.59666e+06
[35]	valid_0's l1: 1.59503e+06
[36]	valid_0's l1: 1.5944e+06
[37]	valid_0's l1: 1.59336e+06
[38]	valid_0's l1: 1.59277e+06
[39]	valid_0's l1: 1.58696e+06
[40]	valid_0's l1: 1.58668e+06
[41]	valid_0's l1: 1.58367e+06
[42]	valid_0's l1: 1.58363e+06
[43]	valid_0's l1: 1.58274e+06
[44]	valid_0's l1: 1.57959e+06
[45]	valid_0's l1: 1.58042e+06
[46]	valid_0's l1: 1.58166e+06
[47]	valid_0's l1: 1.57879e+06
[48]	valid_0's l1: 1.57911e+06
[49]	valid_0's l1: 1.58157e+06
[50]	valid_0's l1: 1.58284e+06
[51]	valid_0's l1: 1.58312e+06
[52]	valid_0's l1: 1.57803e+06
[53]	valid_0's l1: 1.57922e+06
[54]	valid_0's l1: 1.58002e+06
[55]	valid_0's l1: 1.58115e+06
[56]	valid_0's l1: 1.58287e+06
[57]	valid_0's l1: 1.58232e+06
[58]	valid_0's l1: 1.58297e+06
[59]	valid_0's l1: 1.58295e+06
[60]	valid_0's l1: 1.58504e+06
[61]	valid_0's l1: 1.58515e+06
[62]	valid_0's l1: 1.58561e+06
[63]	valid_0's l1: 1.58709e+06
[64]	valid_0's l1: 1.58507e+06
[65]	valid_0's l1: 1.58536e+06
[66]	valid_0's l1: 1.58432e+06
[67]	valid_0's l1: 1.58613e+06
[68]	valid_0's l1: 1.58538e+06
[69]	valid_0's l1: 1.58021e+06
[70]	valid_0's l1: 1.5804e+06
[71]	valid_0's l1: 1.58138e+06
[72]	valid_0's l1: 1.58121e+06
[73]	valid_0's l1: 1.58254e+06
[74]	valid_0's l1: 1.58233e+06
[75]	valid_0's l1: 1.58032e+06
[76]	valid_0's l1: 1.58063e+06
[77]	valid_0's l1: 1.58148e+06
[78]	valid_0's l1: 1.57924e+06
[79]	valid_0's l1: 1.58047e+06
[80]	valid_0's l1: 1.58135e+06
[81]	valid_0's l1: 1.57956e+06
[82]	valid_0's l1: 1.57943e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.57803e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.84197e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.55342e+06
[3]	valid_0's l1: 3.29726e+06
[4]	valid_0's l1: 3.06367e+06
[5]	valid_0's l1: 2.86201e+06
[6]	valid_0's l1: 2.77263e+06
[7]	valid_0's l1: 2.69511e+06
[8]	valid_0's l1: 2.54647e+06
[9]	valid_0's l1: 2.41522e+06
[10]	valid_0's l1: 2.30494e+06
[11]	valid_0's l1: 2.20889e+06
[12]	valid_0's l1: 2.16019e+06
[13]	valid_0's l1: 2.08103e+06
[14]	valid_0's l1: 2.05287e+06
[15]	valid_0's l1: 1.98986e+06
[16]	valid_0's l1: 1.93642e+06
[17]	valid_0's l1: 1.89289e+06
[18]	valid_0's l1: 1.8552e+06
[19]	valid_0's l1: 1.82202e+06
[20]	valid_0's l1: 1.79212e+06
[21]	valid_0's l1: 1.76743e+06
[22]	valid_0's l1: 1.74428e+06
[23]	valid_0's l1: 1.72953e+06
[24]	valid_0's l1: 1.71457e+06
[25]	valid_0's l1: 1.70052e+06
[26]	valid_0's l1: 1.68713e+06
[27]	valid_0's l1: 1.67176e+06
[28]	valid_0's l1: 1.6637e+06
[29]	valid_0's l1: 1.6565e+06
[30]	valid_0's l1: 1.64877e+06
[31]	valid_0's l1: 1.63661e+06
[32]	valid_0's l1: 1.62954e+06
[33]	valid_0's l1: 1.62726e+06
[34]	valid_0's l1: 1.61977e+06
[35]	valid_0's l1: 1.61731e+06
[36]	valid_0's l1: 1.60926e+06
[37]	valid_0's l1: 1.60815e+06
[38]	valid_0's l1: 1.60559e+06
[39]	valid_0's l1: 1.60279e+06
[40]	valid_0's l1: 1.6027e+06
[41]	valid_0's l1: 1.59799e+06
[42]	valid_0's l1: 1.59741e+06
[43]	valid_0's l1: 1.59672e+06
[44]	valid_0's l1: 1.5961e+06
[45]	valid_0's l1: 1.59397e+06
[46]	valid_0's l1: 1.59023e+06
[47]	valid_0's l1: 1.58949e+06
[48]	valid_0's l1: 1.58952e+06
[49]	valid_0's l1: 1.58677e+06
[50]	valid_0's l1: 1.58555e+06
[51]	valid_0's l1: 1.58606e+06
[52]	valid_0's l1: 1.58418e+06
[53]	valid_0's l1: 1.58507e+06
[54]	valid_0's l1: 1.58497e+06
[55]	valid_0's l1: 1.58581e+06
[56]	valid_0's l1: 1.58421e+06
[57]	valid_0's l1: 1.58225e+06
[58]	valid_0's l1: 1.5824e+06
[59]	valid_0's l1: 1.58158e+06
[60]	valid_0's l1: 1.58005e+06
[61]	valid_0's l1: 1.58137e+06
[62]	valid_0's l1: 1.58155e+06
[63]	valid_0's l1: 1.58091e+06
[64]	valid_0's l1: 1.58157e+06
[65]	valid_0's l1: 1.58289e+06
[66]	valid_0's l1: 1.58426e+06
[67]	valid_0's l1: 1.5831e+06
[68]	valid_0's l1: 1.58122e+06
[69]	valid_0's l1: 1.58157e+06
[70]	valid_0's l1: 1.58213e+06
[71]	valid_0's l1: 1.58303e+06
[72]	valid_0's l1: 1.58277e+06
[73]	valid_0's l1: 1.58444e+06
[74]	valid_0's l1: 1.58325e+06
[75]	valid_0's l1: 1.58386e+06
[76]	valid_0's l1: 1.58379e+06
[77]	valid_0's l1: 1.58402e+06
[78]	valid_0's l1: 1.58249e+06
[79]	valid_0's l1: 1.58142e+06
[80]	valid_0's l1: 1.58035e+06
[81]	valid_0's l1: 1.5809e+06
[82]	valid_0's l1: 1.57963e+06
[83]	valid_0's l1: 1.58035e+06
[84]	valid_0's l1: 1.57931e+06
[85]	valid_0's l1: 1.58015e+06
[86]	valid_0's l1: 1.57969e+06
[87]	valid_0's l1: 1.57984e+06
[88]	valid_0's l1: 1.58188e+06
[89]	valid_0's l1: 1.58304e+06
[90]	valid_0's l1: 1.58135e+06
[91]	valid_0's l1: 1.58232e+06
[92]	valid_0's l1: 1.58257e+06
[93]	valid_0's l1: 1.58241e+06
[94]	valid_0's l1: 1.58202e+06
[95]	valid_0's l1: 1.5829e+06
[96]	valid_0's l1: 1.58211e+06
[97]	valid_0's l1: 1.58216e+06
[98]	valid_0's l1: 1.58011e+06
[99]	valid_0's l1: 1.58153e+06
[100]	valid_0's l1: 1.58087e+06
[101]	valid_0's l1: 1.58134e+06
[102]	valid_0's l1: 1.58232e+06
[103]	valid_0's l1: 1.58281e+06
[104]	valid_0's l1: 1.58261e+06
[105]	valid_0's l1: 1.58244e+06
[106]	valid_0's l1: 1.58099e+06
[107]	valid_0's l1: 1.58132e+06
[108]	valid_0's l1: 1.58327e+06
[109]	valid_0's l1: 1.58179e+06
[110]	valid_0's l1: 1.58224e+06
[111]	valid_0's l1: 1.58337e+06
[112]	valid_0's l1: 1.58372e+06
[113]	valid_0's l1: 1.58488e+06
[114]	valid_0's l1: 1.58443e+06
Early stopping, best iteration is:
[84]	valid_0's l1: 1.57931e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.92163e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.62051e+06
[3]	valid_0's l1: 3.34817e+06
[4]	valid_0's l1: 3.11253e+06
[5]	valid_0's l1: 2.90409e+06
[6]	valid_0's l1: 2.80635e+06
[7]	valid_0's l1: 2.7208e+06
[8]	valid_0's l1: 2.56756e+06
[9]	valid_0's l1: 2.43616e+06
[10]	valid_0's l1: 2.32151e+06
[11]	valid_0's l1: 2.21898e+06
[12]	valid_0's l1: 2.17242e+06
[13]	valid_0's l1: 2.09115e+06
[14]	valid_0's l1: 2.06811e+06
[15]	valid_0's l1: 2.00714e+06
[16]	valid_0's l1: 1.95139e+06
[17]	valid_0's l1: 1.90248e+06
[18]	valid_0's l1: 1.86218e+06
[19]	valid_0's l1: 1.8302e+06
[20]	valid_0's l1: 1.79563e+06
[21]	valid_0's l1: 1.76865e+06
[22]	valid_0's l1: 1.7457e+06
[23]	valid_0's l1: 1.72433e+06
[24]	valid_0's l1: 1.70488e+06
[25]	valid_0's l1: 1.69042e+06
[26]	valid_0's l1: 1.67479e+06
[27]	valid_0's l1: 1.66188e+06
[28]	valid_0's l1: 1.65166e+06
[29]	valid_0's l1: 1.64814e+06
[30]	valid_0's l1: 1.64016e+06
[31]	valid_0's l1: 1.63678e+06
[32]	valid_0's l1: 1.6258e+06
[33]	valid_0's l1: 1.62234e+06
[34]	valid_0's l1: 1.6162e+06
[35]	valid_0's l1: 1.61559e+06
[36]	valid_0's l1: 1.61593e+06
[37]	valid_0's l1: 1.61618e+06
[38]	valid_0's l1: 1.61257e+06
[39]	valid_0's l1: 1.61192e+06
[40]	valid_0's l1: 1.61066e+06
[41]	valid_0's l1: 1.6056e+06
[42]	valid_0's l1: 1.60543e+06
[43]	valid_0's l1: 1.60025e+06
[44]	valid_0's l1: 1.59933e+06
[45]	valid_0's l1: 1.59983e+06
[46]	valid_0's l1: 1.598e+06
[47]	valid_0's l1: 1.5973e+06
[48]	valid_0's l1: 1.59616e+06
[49]	valid_0's l1: 1.59576e+06
[50]	valid_0's l1: 1.59615e+06
[51]	valid_0's l1: 1.59734e+06
[52]	valid_0's l1: 1.59782e+06
[53]	valid_0's l1: 1.59771e+06
[54]	valid_0's l1: 1.60004e+06
[55]	valid_0's l1: 1.59929e+06
[56]	valid_0's l1: 1.59945e+06
[57]	valid_0's l1: 1.59901e+06
[58]	valid_0's l1: 1.59883e+06
[59]	valid_0's l1: 1.59938e+06
[60]	valid_0's l1: 1.5966e+06
[61]	valid_0's l1: 1.59638e+06
[62]	valid_0's l1: 1.59613e+06
[63]	valid_0's l1: 1.5968e+06
[64]	valid_0's l1: 1.59515e+06
[65]	valid_0's l1: 1.59466e+06
[66]	valid_0's l1: 1.59371e+06
[67]	valid_0's l1: 1.59335e+06
[68]	valid_0's l1: 1.59401e+06
[69]	valid_0's l1: 1.59414e+06
[70]	valid_0's l1: 1.59451e+06
[71]	valid_0's l1: 1.59378e+06
[72]	valid_0's l1: 1.59398e+06
[73]	valid_0's l1: 1.59567e+06
[74]	valid_0's l1: 1.59669e+06
[75]	valid_0's l1: 1.59692e+06
[76]	valid_0's l1: 1.59488e+06
[77]	valid_0's l1: 1.59495e+06
[78]	valid_0's l1: 1.59601e+06
[79]	valid_0's l1: 1.59527e+06
[80]	valid_0's l1: 1.59578e+06
[81]	valid_0's l1: 1.59741e+06
[82]	valid_0's l1: 1.59656e+06
[83]	valid_0's l1: 1.59728e+06
[84]	valid_0's l1: 1.59658e+06
[85]	valid_0's l1: 1.59677e+06
[86]	valid_0's l1: 1.59746e+06
[87]	valid_0's l1: 1.59818e+06
[88]	valid_0's l1: 1.59816e+06
[89]	valid_0's l1: 1.59824e+06
[90]	valid_0's l1: 1.5967e+06
[91]	valid_0's l1: 1.59675e+06
[92]	valid_0's l1: 1.59634e+06
[93]	valid_0's l1: 1.59721e+06
[94]	valid_0's l1: 1.59734e+06
[95]	valid_0's l1: 1.59877e+06
[96]	valid_0's l1: 1.59858e+06
[97]	valid_0's l1: 1.59878e+06
Early stopping, best iteration is:
[67]	valid_0's l1: 1.59335e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90081e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.59582e+06
[3]	valid_0's l1: 3.33132e+06
[4]	valid_0's l1: 3.098e+06
[5]	valid_0's l1: 2.89114e+06
[6]	valid_0's l1: 2.80556e+06
[7]	valid_0's l1: 2.72592e+06
[8]	valid_0's l1: 2.58085e+06
[9]	valid_0's l1: 2.45021e+06
[10]	valid_0's l1: 2.33527e+06
[11]	valid_0's l1: 2.2391e+06
[12]	valid_0's l1: 2.19693e+06
[13]	valid_0's l1: 2.11329e+06
[14]	valid_0's l1: 2.09066e+06
[15]	valid_0's l1: 2.0198e+06
[16]	valid_0's l1: 1.95972e+06
[17]	valid_0's l1: 1.90723e+06
[18]	valid_0's l1: 1.86494e+06
[19]	valid_0's l1: 1.82292e+06
[20]	valid_0's l1: 1.78873e+06
[21]	valid_0's l1: 1.75883e+06
[22]	valid_0's l1: 1.73505e+06
[23]	valid_0's l1: 1.71207e+06
[24]	valid_0's l1: 1.6975e+06
[25]	valid_0's l1: 1.67955e+06
[26]	valid_0's l1: 1.66097e+06
[27]	valid_0's l1: 1.64628e+06
[28]	valid_0's l1: 1.63646e+06
[29]	valid_0's l1: 1.62795e+06
[30]	valid_0's l1: 1.61504e+06
[31]	valid_0's l1: 1.61319e+06
[32]	valid_0's l1: 1.60404e+06
[33]	valid_0's l1: 1.59766e+06
[34]	valid_0's l1: 1.59666e+06
[35]	valid_0's l1: 1.59503e+06
[36]	valid_0's l1: 1.5944e+06
[37]	valid_0's l1: 1.59336e+06
[38]	valid_0's l1: 1.59277e+06
[39]	valid_0's l1: 1.58696e+06
[40]	valid_0's l1: 1.58668e+06
[41]	valid_0's l1: 1.58367e+06
[42]	valid_0's l1: 1.58363e+06
[43]	valid_0's l1: 1.58274e+06
[44]	valid_0's l1: 1.57959e+06
[45]	valid_0's l1: 1.58042e+06
[46]	valid_0's l1: 1.58166e+06
[47]	valid_0's l1: 1.57879e+06
[48]	valid_0's l1: 1.57911e+06
[49]	valid_0's l1: 1.58157e+06
[50]	valid_0's l1: 1.58284e+06
[51]	valid_0's l1: 1.58312e+06
[52]	valid_0's l1: 1.57803e+06
[53]	valid_0's l1: 1.57922e+06
[54]	valid_0's l1: 1.58002e+06
[55]	valid_0's l1: 1.58115e+06
[56]	valid_0's l1: 1.58287e+06
[57]	valid_0's l1: 1.58232e+06
[58]	valid_0's l1: 1.58297e+06
[59]	valid_0's l1: 1.58295e+06
[60]	valid_0's l1: 1.58504e+06
[61]	valid_0's l1: 1.58515e+06
[62]	valid_0's l1: 1.58561e+06
[63]	valid_0's l1: 1.58709e+06
[64]	valid_0's l1: 1.58507e+06
[65]	valid_0's l1: 1.58536e+06
[66]	valid_0's l1: 1.58432e+06
[67]	valid_0's l1: 1.58613e+06
[68]	valid_0's l1: 1.58538e+06
[69]	valid_0's l1: 1.58021e+06
[70]	valid_0's l1: 1.5804e+06
[71]	valid_0's l1: 1.58138e+06
[72]	valid_0's l1: 1.58121e+06
[73]	valid_0's l1: 1.58254e+06
[74]	valid_0's l1: 1.58233e+06
[75]	valid_0's l1: 1.58032e+06
[76]	valid_0's l1: 1.58063e+06
[77]	valid_0's l1: 1.58148e+06
[78]	valid_0's l1: 1.57924e+06
[79]	valid_0's l1: 1.58047e+06
[80]	valid_0's l1: 1.58135e+06
[81]	valid_0's l1: 1.57956e+06
[82]	valid_0's l1: 1.57943e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.57803e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.84197e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.55342e+06
[3]	valid_0's l1: 3.29726e+06
[4]	valid_0's l1: 3.06367e+06
[5]	valid_0's l1: 2.86201e+06
[6]	valid_0's l1: 2.77263e+06
[7]	valid_0's l1: 2.69511e+06
[8]	valid_0's l1: 2.54647e+06
[9]	valid_0's l1: 2.41522e+06
[10]	valid_0's l1: 2.30494e+06
[11]	valid_0's l1: 2.20889e+06
[12]	valid_0's l1: 2.16019e+06
[13]	valid_0's l1: 2.08103e+06
[14]	valid_0's l1: 2.05287e+06
[15]	valid_0's l1: 1.98986e+06
[16]	valid_0's l1: 1.93642e+06
[17]	valid_0's l1: 1.89289e+06
[18]	valid_0's l1: 1.8552e+06
[19]	valid_0's l1: 1.82202e+06
[20]	valid_0's l1: 1.79212e+06
[21]	valid_0's l1: 1.76743e+06
[22]	valid_0's l1: 1.74428e+06
[23]	valid_0's l1: 1.72953e+06
[24]	valid_0's l1: 1.71457e+06
[25]	valid_0's l1: 1.70052e+06
[26]	valid_0's l1: 1.68713e+06
[27]	valid_0's l1: 1.67176e+06
[28]	valid_0's l1: 1.6637e+06
[29]	valid_0's l1: 1.6565e+06
[30]	valid_0's l1: 1.64877e+06
[31]	valid_0's l1: 1.63661e+06
[32]	valid_0's l1: 1.62954e+06
[33]	valid_0's l1: 1.62726e+06
[34]	valid_0's l1: 1.61977e+06
[35]	valid_0's l1: 1.61731e+06
[36]	valid_0's l1: 1.60926e+06
[37]	valid_0's l1: 1.60815e+06
[38]	valid_0's l1: 1.60559e+06
[39]	valid_0's l1: 1.60279e+06
[40]	valid_0's l1: 1.6027e+06
[41]	valid_0's l1: 1.59799e+06
[42]	valid_0's l1: 1.59741e+06
[43]	valid_0's l1: 1.59672e+06
[44]	valid_0's l1: 1.5961e+06
[45]	valid_0's l1: 1.59397e+06
[46]	valid_0's l1: 1.59023e+06
[47]	valid_0's l1: 1.58949e+06
[48]	valid_0's l1: 1.58952e+06
[49]	valid_0's l1: 1.58677e+06
[50]	valid_0's l1: 1.58555e+06
[51]	valid_0's l1: 1.58606e+06
[52]	valid_0's l1: 1.58418e+06
[53]	valid_0's l1: 1.58507e+06
[54]	valid_0's l1: 1.58497e+06
[55]	valid_0's l1: 1.58581e+06
[56]	valid_0's l1: 1.58421e+06
[57]	valid_0's l1: 1.58225e+06
[58]	valid_0's l1: 1.5824e+06
[59]	valid_0's l1: 1.58158e+06
[60]	valid_0's l1: 1.58005e+06
[61]	valid_0's l1: 1.58137e+06
[62]	valid_0's l1: 1.58155e+06
[63]	valid_0's l1: 1.58091e+06
[64]	valid_0's l1: 1.58157e+06
[65]	valid_0's l1: 1.58289e+06
[66]	valid_0's l1: 1.58426e+06
[67]	valid_0's l1: 1.5831e+06
[68]	valid_0's l1: 1.58122e+06
[69]	valid_0's l1: 1.58157e+06
[70]	valid_0's l1: 1.58213e+06
[71]	valid_0's l1: 1.58303e+06
[72]	valid_0's l1: 1.58277e+06
[73]	valid_0's l1: 1.58444e+06
[74]	valid_0's l1: 1.58325e+06
[75]	valid_0's l1: 1.58386e+06
[76]	valid_0's l1: 1.58379e+06
[77]	valid_0's l1: 1.58402e+06
[78]	valid_0's l1: 1.58249e+06
[79]	valid_0's l1: 1.58142e+06
[80]	valid_0's l1: 1.58035e+06
[81]	valid_0's l1: 1.5809e+06
[82]	valid_0's l1: 1.57963e+06
[83]	valid_0's l1: 1.58035e+06
[84]	valid_0's l1: 1.57931e+06
[85]	valid_0's l1: 1.58015e+06
[86]	valid_0's l1: 1.57969e+06
[87]	valid_0's l1: 1.57984e+06
[88]	valid_0's l1: 1.58188e+06
[89]	valid_0's l1: 1.58304e+06
[90]	valid_0's l1: 1.58135e+06
[91]	valid_0's l1: 1.58232e+06
[92]	valid_0's l1: 1.58257e+06
[93]	valid_0's l1: 1.58241e+06
[94]	valid_0's l1: 1.58202e+06
[95]	valid_0's l1: 1.5829e+06
[96]	valid_0's l1: 1.58211e+06
[97]	valid_0's l1: 1.58216e+06
[98]	valid_0's l1: 1.58011e+06
[99]	valid_0's l1: 1.58153e+06
[100]	valid_0's l1: 1.58087e+06
[101]	valid_0's l1: 1.58134e+06
[102]	valid_0's l1: 1.58232e+06
[103]	valid_0's l1: 1.58281e+06
[104]	valid_0's l1: 1.58261e+06
[105]	valid_0's l1: 1.58244e+06
[106]	valid_0's l1: 1.58099e+06
[107]	valid_0's l1: 1.58132e+06
[108]	valid_0's l1: 1.58327e+06
[109]	valid_0's l1: 1.58179e+06
[110]	valid_0's l1: 1.58224e+06
[111]	valid_0's l1: 1.58337e+06
[112]	valid_0's l1: 1.58372e+06
[113]	valid_0's l1: 1.58488e+06
[114]	valid_0's l1: 1.58443e+06
Early stopping, best iteration is:
[84]	valid_0's l1: 1.57931e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.92163e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.62051e+06
[3]	valid_0's l1: 3.34817e+06
[4]	valid_0's l1: 3.11253e+06
[5]	valid_0's l1: 2.90409e+06
[6]	valid_0's l1: 2.80635e+06
[7]	valid_0's l1: 2.7208e+06
[8]	valid_0's l1: 2.56756e+06
[9]	valid_0's l1: 2.43616e+06
[10]	valid_0's l1: 2.32151e+06
[11]	valid_0's l1: 2.21898e+06
[12]	valid_0's l1: 2.17242e+06
[13]	valid_0's l1: 2.09115e+06
[14]	valid_0's l1: 2.06811e+06
[15]	valid_0's l1: 2.00714e+06
[16]	valid_0's l1: 1.95139e+06
[17]	valid_0's l1: 1.90248e+06
[18]	valid_0's l1: 1.86218e+06
[19]	valid_0's l1: 1.8302e+06
[20]	valid_0's l1: 1.79563e+06
[21]	valid_0's l1: 1.76865e+06
[22]	valid_0's l1: 1.7457e+06
[23]	valid_0's l1: 1.72433e+06
[24]	valid_0's l1: 1.70488e+06
[25]	valid_0's l1: 1.69042e+06
[26]	valid_0's l1: 1.67479e+06
[27]	valid_0's l1: 1.66188e+06
[28]	valid_0's l1: 1.65166e+06
[29]	valid_0's l1: 1.64814e+06
[30]	valid_0's l1: 1.64016e+06
[31]	valid_0's l1: 1.63678e+06
[32]	valid_0's l1: 1.6258e+06
[33]	valid_0's l1: 1.62234e+06
[34]	valid_0's l1: 1.6162e+06
[35]	valid_0's l1: 1.61559e+06
[36]	valid_0's l1: 1.61593e+06
[37]	valid_0's l1: 1.61618e+06
[38]	valid_0's l1: 1.61257e+06
[39]	valid_0's l1: 1.61192e+06
[40]	valid_0's l1: 1.61066e+06
[41]	valid_0's l1: 1.6056e+06
[42]	valid_0's l1: 1.60543e+06
[43]	valid_0's l1: 1.60025e+06
[44]	valid_0's l1: 1.59933e+06
[45]	valid_0's l1: 1.59983e+06
[46]	valid_0's l1: 1.598e+06
[47]	valid_0's l1: 1.5973e+06
[48]	valid_0's l1: 1.59616e+06
[49]	valid_0's l1: 1.59576e+06
[50]	valid_0's l1: 1.59615e+06
[51]	valid_0's l1: 1.59734e+06
[52]	valid_0's l1: 1.59782e+06
[53]	valid_0's l1: 1.59771e+06
[54]	valid_0's l1: 1.60004e+06
[55]	valid_0's l1: 1.59929e+06
[56]	valid_0's l1: 1.59945e+06
[57]	valid_0's l1: 1.59901e+06
[58]	valid_0's l1: 1.59883e+06
[59]	valid_0's l1: 1.59938e+06
[60]	valid_0's l1: 1.5966e+06
[61]	valid_0's l1: 1.59638e+06
[62]	valid_0's l1: 1.59613e+06
[63]	valid_0's l1: 1.5968e+06
[64]	valid_0's l1: 1.59515e+06
[65]	valid_0's l1: 1.59466e+06
[66]	valid_0's l1: 1.59371e+06
[67]	valid_0's l1: 1.59335e+06
[68]	valid_0's l1: 1.59401e+06
[69]	valid_0's l1: 1.59414e+06
[70]	valid_0's l1: 1.59451e+06
[71]	valid_0's l1: 1.59378e+06
[72]	valid_0's l1: 1.59398e+06
[73]	valid_0's l1: 1.59567e+06
[74]	valid_0's l1: 1.59669e+06
[75]	valid_0's l1: 1.59692e+06
[76]	valid_0's l1: 1.59488e+06
[77]	valid_0's l1: 1.59495e+06
[78]	valid_0's l1: 1.59601e+06
[79]	valid_0's l1: 1.59527e+06
[80]	valid_0's l1: 1.59578e+06
[81]	valid_0's l1: 1.59741e+06
[82]	valid_0's l1: 1.59656e+06
[83]	valid_0's l1: 1.59728e+06
[84]	valid_0's l1: 1.59658e+06
[85]	valid_0's l1: 1.59677e+06
[86]	valid_0's l1: 1.59746e+06
[87]	valid_0's l1: 1.59818e+06
[88]	valid_0's l1: 1.59816e+06
[89]	valid_0's l1: 1.59824e+06
[90]	valid_0's l1: 1.5967e+06
[91]	valid_0's l1: 1.59675e+06
[92]	valid_0's l1: 1.59634e+06
[93]	valid_0's l1: 1.59721e+06
[94]	valid_0's l1: 1.59734e+06
[95]	valid_0's l1: 1.59877e+06
[96]	valid_0's l1: 1.59858e+06
[97]	valid_0's l1: 1.59878e+06
Early stopping, best iteration is:
[67]	valid_0's l1: 1.59335e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.90081e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.59582e+06
[3]	valid_0's l1: 3.33132e+06
[4]	valid_0's l1: 3.098e+06
[5]	valid_0's l1: 2.89114e+06
[6]	valid_0's l1: 2.80556e+06
[7]	valid_0's l1: 2.72592e+06
[8]	valid_0's l1: 2.58085e+06
[9]	valid_0's l1: 2.45021e+06
[10]	valid_0's l1: 2.33527e+06
[11]	valid_0's l1: 2.2391e+06
[12]	valid_0's l1: 2.19693e+06
[13]	valid_0's l1: 2.11329e+06
[14]	valid_0's l1: 2.09066e+06
[15]	valid_0's l1: 2.0198e+06
[16]	valid_0's l1: 1.95972e+06
[17]	valid_0's l1: 1.90723e+06
[18]	valid_0's l1: 1.86494e+06
[19]	valid_0's l1: 1.82292e+06
[20]	valid_0's l1: 1.78873e+06
[21]	valid_0's l1: 1.75883e+06
[22]	valid_0's l1: 1.73505e+06
[23]	valid_0's l1: 1.71207e+06
[24]	valid_0's l1: 1.6975e+06
[25]	valid_0's l1: 1.67955e+06
[26]	valid_0's l1: 1.66097e+06
[27]	valid_0's l1: 1.64628e+06
[28]	valid_0's l1: 1.63646e+06
[29]	valid_0's l1: 1.62795e+06
[30]	valid_0's l1: 1.61504e+06
[31]	valid_0's l1: 1.61319e+06
[32]	valid_0's l1: 1.60404e+06
[33]	valid_0's l1: 1.59766e+06
[34]	valid_0's l1: 1.59666e+06
[35]	valid_0's l1: 1.59503e+06
[36]	valid_0's l1: 1.5944e+06
[37]	valid_0's l1: 1.59336e+06
[38]	valid_0's l1: 1.59277e+06
[39]	valid_0's l1: 1.58696e+06
[40]	valid_0's l1: 1.58668e+06
[41]	valid_0's l1: 1.58367e+06
[42]	valid_0's l1: 1.58363e+06
[43]	valid_0's l1: 1.58274e+06
[44]	valid_0's l1: 1.57959e+06
[45]	valid_0's l1: 1.58042e+06
[46]	valid_0's l1: 1.58166e+06
[47]	valid_0's l1: 1.57879e+06
[48]	valid_0's l1: 1.57911e+06
[49]	valid_0's l1: 1.58157e+06
[50]	valid_0's l1: 1.58284e+06
[51]	valid_0's l1: 1.58312e+06
[52]	valid_0's l1: 1.57803e+06
[53]	valid_0's l1: 1.57922e+06
[54]	valid_0's l1: 1.58002e+06
[55]	valid_0's l1: 1.58115e+06
[56]	valid_0's l1: 1.58287e+06
[57]	valid_0's l1: 1.58232e+06
[58]	valid_0's l1: 1.58297e+06
[59]	valid_0's l1: 1.58295e+06
[60]	valid_0's l1: 1.58504e+06
[61]	valid_0's l1: 1.58515e+06
[62]	valid_0's l1: 1.58561e+06
[63]	valid_0's l1: 1.58709e+06
[64]	valid_0's l1: 1.58507e+06
[65]	valid_0's l1: 1.58536e+06
[66]	valid_0's l1: 1.58432e+06
[67]	valid_0's l1: 1.58613e+06
[68]	valid_0's l1: 1.58538e+06
[69]	valid_0's l1: 1.58021e+06
[70]	valid_0's l1: 1.5804e+06
[71]	valid_0's l1: 1.58138e+06
[72]	valid_0's l1: 1.58121e+06
[73]	valid_0's l1: 1.58254e+06
[74]	valid_0's l1: 1.58233e+06
[75]	valid_0's l1: 1.58032e+06
[76]	valid_0's l1: 1.58063e+06
[77]	valid_0's l1: 1.58148e+06
[78]	valid_0's l1: 1.57924e+06
[79]	valid_0's l1: 1.58047e+06
[80]	valid_0's l1: 1.58135e+06
[81]	valid_0's l1: 1.57956e+06
[82]	valid_0's l1: 1.57943e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.57803e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.84197e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.55342e+06
[3]	valid_0's l1: 3.29726e+06
[4]	valid_0's l1: 3.06367e+06
[5]	valid_0's l1: 2.86201e+06
[6]	valid_0's l1: 2.77263e+06
[7]	valid_0's l1: 2.69511e+06
[8]	valid_0's l1: 2.54647e+06
[9]	valid_0's l1: 2.41522e+06
[10]	valid_0's l1: 2.30494e+06
[11]	valid_0's l1: 2.20889e+06
[12]	valid_0's l1: 2.16019e+06
[13]	valid_0's l1: 2.08103e+06
[14]	valid_0's l1: 2.05287e+06
[15]	valid_0's l1: 1.98986e+06
[16]	valid_0's l1: 1.93642e+06
[17]	valid_0's l1: 1.89289e+06
[18]	valid_0's l1: 1.8552e+06
[19]	valid_0's l1: 1.82202e+06
[20]	valid_0's l1: 1.79212e+06
[21]	valid_0's l1: 1.76743e+06
[22]	valid_0's l1: 1.74428e+06
[23]	valid_0's l1: 1.72953e+06
[24]	valid_0's l1: 1.71457e+06
[25]	valid_0's l1: 1.70052e+06
[26]	valid_0's l1: 1.68713e+06
[27]	valid_0's l1: 1.67176e+06
[28]	valid_0's l1: 1.6637e+06
[29]	valid_0's l1: 1.6565e+06
[30]	valid_0's l1: 1.64877e+06
[31]	valid_0's l1: 1.63661e+06
[32]	valid_0's l1: 1.62954e+06
[33]	valid_0's l1: 1.62726e+06
[34]	valid_0's l1: 1.61977e+06
[35]	valid_0's l1: 1.61731e+06
[36]	valid_0's l1: 1.60926e+06
[37]	valid_0's l1: 1.60815e+06
[38]	valid_0's l1: 1.60559e+06
[39]	valid_0's l1: 1.60279e+06
[40]	valid_0's l1: 1.6027e+06
[41]	valid_0's l1: 1.59799e+06
[42]	valid_0's l1: 1.59741e+06
[43]	valid_0's l1: 1.59672e+06
[44]	valid_0's l1: 1.5961e+06
[45]	valid_0's l1: 1.59397e+06
[46]	valid_0's l1: 1.59023e+06
[47]	valid_0's l1: 1.58949e+06
[48]	valid_0's l1: 1.58952e+06
[49]	valid_0's l1: 1.58677e+06
[50]	valid_0's l1: 1.58555e+06
[51]	valid_0's l1: 1.58606e+06
[52]	valid_0's l1: 1.58418e+06
[53]	valid_0's l1: 1.58507e+06
[54]	valid_0's l1: 1.58497e+06
[55]	valid_0's l1: 1.58581e+06
[56]	valid_0's l1: 1.58421e+06
[57]	valid_0's l1: 1.58225e+06
[58]	valid_0's l1: 1.5824e+06
[59]	valid_0's l1: 1.58158e+06
[60]	valid_0's l1: 1.58005e+06
[61]	valid_0's l1: 1.58137e+06
[62]	valid_0's l1: 1.58155e+06
[63]	valid_0's l1: 1.58091e+06
[64]	valid_0's l1: 1.58157e+06
[65]	valid_0's l1: 1.58289e+06
[66]	valid_0's l1: 1.58426e+06
[67]	valid_0's l1: 1.5831e+06
[68]	valid_0's l1: 1.58122e+06
[69]	valid_0's l1: 1.58157e+06
[70]	valid_0's l1: 1.58213e+06
[71]	valid_0's l1: 1.58303e+06
[72]	valid_0's l1: 1.58277e+06
[73]	valid_0's l1: 1.58444e+06
[74]	valid_0's l1: 1.58325e+06
[75]	valid_0's l1: 1.58386e+06
[76]	valid_0's l1: 1.58379e+06
[77]	valid_0's l1: 1.58402e+06
[78]	valid_0's l1: 1.58249e+06
[79]	valid_0's l1: 1.58142e+06
[80]	valid_0's l1: 1.58035e+06
[81]	valid_0's l1: 1.5809e+06
[82]	valid_0's l1: 1.57963e+06
[83]	valid_0's l1: 1.58035e+06
[84]	valid_0's l1: 1.57931e+06
[85]	valid_0's l1: 1.58015e+06
[86]	valid_0's l1: 1.57969e+06
[87]	valid_0's l1: 1.57984e+06
[88]	valid_0's l1: 1.58188e+06
[89]	valid_0's l1: 1.58304e+06
[90]	valid_0's l1: 1.58135e+06
[91]	valid_0's l1: 1.58232e+06
[92]	valid_0's l1: 1.58257e+06
[93]	valid_0's l1: 1.58241e+06
[94]	valid_0's l1: 1.58202e+06
[95]	valid_0's l1: 1.5829e+06
[96]	valid_0's l1: 1.58211e+06
[97]	valid_0's l1: 1.58216e+06
[98]	valid_0's l1: 1.58011e+06
[99]	valid_0's l1: 1.58153e+06
[100]	valid_0's l1: 1.58087e+06
[101]	valid_0's l1: 1.58134e+06
[102]	valid_0's l1: 1.58232e+06
[103]	valid_0's l1: 1.58281e+06
[104]	valid_0's l1: 1.58261e+06
[105]	valid_0's l1: 1.58244e+06
[106]	valid_0's l1: 1.58099e+06
[107]	valid_0's l1: 1.58132e+06
[108]	valid_0's l1: 1.58327e+06
[109]	valid_0's l1: 1.58179e+06
[110]	valid_0's l1: 1.58224e+06
[111]	valid_0's l1: 1.58337e+06
[112]	valid_0's l1: 1.58372e+06
[113]	valid_0's l1: 1.58488e+06
[114]	valid_0's l1: 1.58443e+06
Early stopping, best iteration is:
[84]	valid_0's l1: 1.57931e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.92163e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.62051e+06
[3]	valid_0's l1: 3.34817e+06
[4]	valid_0's l1: 3.11253e+06
[5]	valid_0's l1: 2.90409e+06
[6]	valid_0's l1: 2.80635e+06
[7]	valid_0's l1: 2.7208e+06
[8]	valid_0's l1: 2.56756e+06
[9]	valid_0's l1: 2.43616e+06
[10]	valid_0's l1: 2.32151e+06
[11]	valid_0's l1: 2.21898e+06
[12]	valid_0's l1: 2.17242e+06
[13]	valid_0's l1: 2.09115e+06
[14]	valid_0's l1: 2.06811e+06
[15]	valid_0's l1: 2.00714e+06
[16]	valid_0's l1: 1.95139e+06
[17]	valid_0's l1: 1.90248e+06
[18]	valid_0's l1: 1.86218e+06
[19]	valid_0's l1: 1.8302e+06
[20]	valid_0's l1: 1.79563e+06
[21]	valid_0's l1: 1.76865e+06
[22]	valid_0's l1: 1.7457e+06
[23]	valid_0's l1: 1.72433e+06
[24]	valid_0's l1: 1.70488e+06
[25]	valid_0's l1: 1.69042e+06
[26]	valid_0's l1: 1.67479e+06
[27]	valid_0's l1: 1.66188e+06
[28]	valid_0's l1: 1.65166e+06
[29]	valid_0's l1: 1.64814e+06
[30]	valid_0's l1: 1.64016e+06
[31]	valid_0's l1: 1.63678e+06
[32]	valid_0's l1: 1.6258e+06
[33]	valid_0's l1: 1.62234e+06
[34]	valid_0's l1: 1.6162e+06
[35]	valid_0's l1: 1.61559e+06
[36]	valid_0's l1: 1.61593e+06
[37]	valid_0's l1: 1.61618e+06
[38]	valid_0's l1: 1.61257e+06
[39]	valid_0's l1: 1.61192e+06
[40]	valid_0's l1: 1.61066e+06
[41]	valid_0's l1: 1.6056e+06
[42]	valid_0's l1: 1.60543e+06
[43]	valid_0's l1: 1.60025e+06
[44]	valid_0's l1: 1.59933e+06
[45]	valid_0's l1: 1.59983e+06
[46]	valid_0's l1: 1.598e+06
[47]	valid_0's l1: 1.5973e+06
[48]	valid_0's l1: 1.59616e+06
[49]	valid_0's l1: 1.59576e+06
[50]	valid_0's l1: 1.59615e+06
[51]	valid_0's l1: 1.59734e+06
[52]	valid_0's l1: 1.59782e+06
[53]	valid_0's l1: 1.59771e+06
[54]	valid_0's l1: 1.60004e+06
[55]	valid_0's l1: 1.59929e+06
[56]	valid_0's l1: 1.59945e+06
[57]	valid_0's l1: 1.59901e+06
[58]	valid_0's l1: 1.59883e+06
[59]	valid_0's l1: 1.59938e+06
[60]	valid_0's l1: 1.5966e+06
[61]	valid_0's l1: 1.59638e+06
[62]	valid_0's l1: 1.59613e+06
[63]	valid_0's l1: 1.5968e+06
[64]	valid_0's l1: 1.59515e+06
[65]	valid_0's l1: 1.59466e+06
[66]	valid_0's l1: 1.59371e+06
[67]	valid_0's l1: 1.59335e+06
[68]	valid_0's l1: 1.59401e+06
[69]	valid_0's l1: 1.59414e+06
[70]	valid_0's l1: 1.59451e+06
[71]	valid_0's l1: 1.59378e+06
[72]	valid_0's l1: 1.59398e+06
[73]	valid_0's l1: 1.59567e+06
[74]	valid_0's l1: 1.59669e+06
[75]	valid_0's l1: 1.59692e+06
[76]	valid_0's l1: 1.59488e+06
[77]	valid_0's l1: 1.59495e+06
[78]	valid_0's l1: 1.59601e+06
[79]	valid_0's l1: 1.59527e+06
[80]	valid_0's l1: 1.59578e+06
[81]	valid_0's l1: 1.59741e+06
[82]	valid_0's l1: 1.59656e+06
[83]	valid_0's l1: 1.59728e+06
[84]	valid_0's l1: 1.59658e+06
[85]	valid_0's l1: 1.59677e+06
[86]	valid_0's l1: 1.59746e+06
[87]	valid_0's l1: 1.59818e+06
[88]	valid_0's l1: 1.59816e+06
[89]	valid_0's l1: 1.59824e+06
[90]	valid_0's l1: 1.5967e+06
[91]	valid_0's l1: 1.59675e+06
[92]	valid_0's l1: 1.59634e+06
[93]	valid_0's l1: 1.59721e+06
[94]	valid_0's l1: 1.59734e+06
[95]	valid_0's l1: 1.59877e+06
[96]	valid_0's l1: 1.59858e+06
[97]	valid_0's l1: 1.59878e+06
Early stopping, best iteration is:
[67]	valid_0's l1: 1.59335e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.893e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58967e+06
[3]	valid_0's l1: 3.32468e+06
[4]	valid_0's l1: 3.09825e+06
[5]	valid_0's l1: 2.89071e+06
[6]	valid_0's l1: 2.80154e+06
[7]	valid_0's l1: 2.71644e+06
[8]	valid_0's l1: 2.56741e+06
[9]	valid_0's l1: 2.43756e+06
[10]	valid_0's l1: 2.32643e+06
[11]	valid_0's l1: 2.23079e+06
[12]	valid_0's l1: 2.18948e+06
[13]	valid_0's l1: 2.10749e+06
[14]	valid_0's l1: 2.08242e+06
[15]	valid_0's l1: 2.01493e+06
[16]	valid_0's l1: 1.95632e+06
[17]	valid_0's l1: 1.90485e+06
[18]	valid_0's l1: 1.86042e+06
[19]	valid_0's l1: 1.82396e+06
[20]	valid_0's l1: 1.79462e+06
[21]	valid_0's l1: 1.76725e+06
[22]	valid_0's l1: 1.7403e+06
[23]	valid_0's l1: 1.71626e+06
[24]	valid_0's l1: 1.69631e+06
[25]	valid_0's l1: 1.67999e+06
[26]	valid_0's l1: 1.66406e+06
[27]	valid_0's l1: 1.65339e+06
[28]	valid_0's l1: 1.64006e+06
[29]	valid_0's l1: 1.63299e+06
[30]	valid_0's l1: 1.63076e+06
[31]	valid_0's l1: 1.6258e+06
[32]	valid_0's l1: 1.62122e+06
[33]	valid_0's l1: 1.616e+06
[34]	valid_0's l1: 1.61383e+06
[35]	valid_0's l1: 1.61383e+06
[36]	valid_0's l1: 1.60584e+06
[37]	valid_0's l1: 1.60486e+06
[38]	valid_0's l1: 1.60448e+06
[39]	valid_0's l1: 1.59697e+06
[40]	valid_0's l1: 1.5953e+06
[41]	valid_0's l1: 1.59587e+06
[42]	valid_0's l1: 1.59189e+06
[43]	valid_0's l1: 1.59228e+06
[44]	valid_0's l1: 1.58958e+06
[45]	valid_0's l1: 1.58835e+06
[46]	valid_0's l1: 1.5905e+06
[47]	valid_0's l1: 1.59163e+06
[48]	valid_0's l1: 1.58945e+06
[49]	valid_0's l1: 1.59093e+06
[50]	valid_0's l1: 1.58741e+06
[51]	valid_0's l1: 1.58842e+06
[52]	valid_0's l1: 1.58895e+06
[53]	valid_0's l1: 1.59036e+06
[54]	valid_0's l1: 1.59301e+06
[55]	valid_0's l1: 1.59183e+06
[56]	valid_0's l1: 1.58957e+06
[57]	valid_0's l1: 1.59206e+06
[58]	valid_0's l1: 1.5917e+06
[59]	valid_0's l1: 1.59371e+06
[60]	valid_0's l1: 1.59457e+06
[61]	valid_0's l1: 1.59512e+06
[62]	valid_0's l1: 1.59525e+06
[63]	valid_0's l1: 1.59274e+06
[64]	valid_0's l1: 1.5912e+06
[65]	valid_0's l1: 1.59183e+06
[66]	valid_0's l1: 1.59296e+06
[67]	valid_0's l1: 1.5923e+06
[68]	valid_0's l1: 1.59439e+06
[69]	valid_0's l1: 1.59513e+06
[70]	valid_0's l1: 1.59526e+06
[71]	valid_0's l1: 1.59688e+06
[72]	valid_0's l1: 1.59705e+06
[73]	valid_0's l1: 1.59793e+06
[74]	valid_0's l1: 1.59769e+06
[75]	valid_0's l1: 1.59656e+06
[76]	valid_0's l1: 1.59516e+06
[77]	valid_0's l1: 1.59735e+06
[78]	valid_0's l1: 1.59631e+06
[79]	valid_0's l1: 1.5967e+06
[80]	valid_0's l1: 1.59598e+06
Early stopping, best iteration is:
[50]	valid_0's l1: 1.58741e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.83364e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.5461e+06
[3]	valid_0's l1: 3.29059e+06
[4]	valid_0's l1: 3.05995e+06
[5]	valid_0's l1: 2.86177e+06
[6]	valid_0's l1: 2.77283e+06
[7]	valid_0's l1: 2.69017e+06
[8]	valid_0's l1: 2.54159e+06
[9]	valid_0's l1: 2.41143e+06
[10]	valid_0's l1: 2.30017e+06
[11]	valid_0's l1: 2.20183e+06
[12]	valid_0's l1: 2.15705e+06
[13]	valid_0's l1: 2.07987e+06
[14]	valid_0's l1: 2.05065e+06
[15]	valid_0's l1: 1.98821e+06
[16]	valid_0's l1: 1.93406e+06
[17]	valid_0's l1: 1.88841e+06
[18]	valid_0's l1: 1.8524e+06
[19]	valid_0's l1: 1.81851e+06
[20]	valid_0's l1: 1.78965e+06
[21]	valid_0's l1: 1.76343e+06
[22]	valid_0's l1: 1.74308e+06
[23]	valid_0's l1: 1.7241e+06
[24]	valid_0's l1: 1.70645e+06
[25]	valid_0's l1: 1.69239e+06
[26]	valid_0's l1: 1.67826e+06
[27]	valid_0's l1: 1.66647e+06
[28]	valid_0's l1: 1.65689e+06
[29]	valid_0's l1: 1.64698e+06
[30]	valid_0's l1: 1.63783e+06
[31]	valid_0's l1: 1.62995e+06
[32]	valid_0's l1: 1.62507e+06
[33]	valid_0's l1: 1.62243e+06
[34]	valid_0's l1: 1.61622e+06
[35]	valid_0's l1: 1.61111e+06
[36]	valid_0's l1: 1.6069e+06
[37]	valid_0's l1: 1.6063e+06
[38]	valid_0's l1: 1.60097e+06
[39]	valid_0's l1: 1.60005e+06
[40]	valid_0's l1: 1.59611e+06
[41]	valid_0's l1: 1.59512e+06
[42]	valid_0's l1: 1.59286e+06
[43]	valid_0's l1: 1.5929e+06
[44]	valid_0's l1: 1.59173e+06
[45]	valid_0's l1: 1.59163e+06
[46]	valid_0's l1: 1.59149e+06
[47]	valid_0's l1: 1.59111e+06
[48]	valid_0's l1: 1.59168e+06
[49]	valid_0's l1: 1.59049e+06
[50]	valid_0's l1: 1.58867e+06
[51]	valid_0's l1: 1.58963e+06
[52]	valid_0's l1: 1.5878e+06
[53]	valid_0's l1: 1.58834e+06
[54]	valid_0's l1: 1.58963e+06
[55]	valid_0's l1: 1.59054e+06
[56]	valid_0's l1: 1.58928e+06
[57]	valid_0's l1: 1.59034e+06
[58]	valid_0's l1: 1.59245e+06
[59]	valid_0's l1: 1.59305e+06
[60]	valid_0's l1: 1.59228e+06
[61]	valid_0's l1: 1.59105e+06
[62]	valid_0's l1: 1.59135e+06
[63]	valid_0's l1: 1.59307e+06
[64]	valid_0's l1: 1.59467e+06
[65]	valid_0's l1: 1.59252e+06
[66]	valid_0's l1: 1.59273e+06
[67]	valid_0's l1: 1.59195e+06
[68]	valid_0's l1: 1.59278e+06
[69]	valid_0's l1: 1.59117e+06
[70]	valid_0's l1: 1.59206e+06
[71]	valid_0's l1: 1.58878e+06
[72]	valid_0's l1: 1.58795e+06
[73]	valid_0's l1: 1.58921e+06
[74]	valid_0's l1: 1.58924e+06
[75]	valid_0's l1: 1.58805e+06
[76]	valid_0's l1: 1.59015e+06
[77]	valid_0's l1: 1.58963e+06
[78]	valid_0's l1: 1.59027e+06
[79]	valid_0's l1: 1.59127e+06
[80]	valid_0's l1: 1.59145e+06
[81]	valid_0's l1: 1.59056e+06
[82]	valid_0's l1: 1.58941e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.5878e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.91572e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.61074e+06
[3]	valid_0's l1: 3.33753e+06
[4]	valid_0's l1: 3.10152e+06
[5]	valid_0's l1: 2.89582e+06
[6]	valid_0's l1: 2.79571e+06
[7]	valid_0's l1: 2.70656e+06
[8]	valid_0's l1: 2.55707e+06
[9]	valid_0's l1: 2.42782e+06
[10]	valid_0's l1: 2.31229e+06
[11]	valid_0's l1: 2.20818e+06
[12]	valid_0's l1: 2.16335e+06
[13]	valid_0's l1: 2.08003e+06
[14]	valid_0's l1: 2.05301e+06
[15]	valid_0's l1: 1.99207e+06
[16]	valid_0's l1: 1.94133e+06
[17]	valid_0's l1: 1.89339e+06
[18]	valid_0's l1: 1.85478e+06
[19]	valid_0's l1: 1.8147e+06
[20]	valid_0's l1: 1.78487e+06
[21]	valid_0's l1: 1.75924e+06
[22]	valid_0's l1: 1.74016e+06
[23]	valid_0's l1: 1.71891e+06
[24]	valid_0's l1: 1.70106e+06
[25]	valid_0's l1: 1.68439e+06
[26]	valid_0's l1: 1.67383e+06
[27]	valid_0's l1: 1.65878e+06
[28]	valid_0's l1: 1.649e+06
[29]	valid_0's l1: 1.63901e+06
[30]	valid_0's l1: 1.62905e+06
[31]	valid_0's l1: 1.62759e+06
[32]	valid_0's l1: 1.61952e+06
[33]	valid_0's l1: 1.61689e+06
[34]	valid_0's l1: 1.61312e+06
[35]	valid_0's l1: 1.60736e+06
[36]	valid_0's l1: 1.60514e+06
[37]	valid_0's l1: 1.60376e+06
[38]	valid_0's l1: 1.60592e+06
[39]	valid_0's l1: 1.60543e+06
[40]	valid_0's l1: 1.59799e+06
[41]	valid_0's l1: 1.59851e+06
[42]	valid_0's l1: 1.59751e+06
[43]	valid_0's l1: 1.59811e+06
[44]	valid_0's l1: 1.59782e+06
[45]	valid_0's l1: 1.59742e+06
[46]	valid_0's l1: 1.59288e+06
[47]	valid_0's l1: 1.59251e+06
[48]	valid_0's l1: 1.59195e+06
[49]	valid_0's l1: 1.58928e+06
[50]	valid_0's l1: 1.59053e+06
[51]	valid_0's l1: 1.59081e+06
[52]	valid_0's l1: 1.59059e+06
[53]	valid_0's l1: 1.59177e+06
[54]	valid_0's l1: 1.59203e+06
[55]	valid_0's l1: 1.59381e+06
[56]	valid_0's l1: 1.59399e+06
[57]	valid_0's l1: 1.59315e+06
[58]	valid_0's l1: 1.59266e+06
[59]	valid_0's l1: 1.59384e+06
[60]	valid_0's l1: 1.59174e+06
[61]	valid_0's l1: 1.58921e+06
[62]	valid_0's l1: 1.58785e+06
[63]	valid_0's l1: 1.58523e+06
[64]	valid_0's l1: 1.58298e+06
[65]	valid_0's l1: 1.58113e+06
[66]	valid_0's l1: 1.58106e+06
[67]	valid_0's l1: 1.58116e+06
[68]	valid_0's l1: 1.57942e+06
[69]	valid_0's l1: 1.58066e+06
[70]	valid_0's l1: 1.58022e+06
[71]	valid_0's l1: 1.5808e+06
[72]	valid_0's l1: 1.58208e+06
[73]	valid_0's l1: 1.58456e+06
[74]	valid_0's l1: 1.58385e+06
[75]	valid_0's l1: 1.58498e+06
[76]	valid_0's l1: 1.58434e+06
[77]	valid_0's l1: 1.58475e+06
[78]	valid_0's l1: 1.58145e+06
[79]	valid_0's l1: 1.58196e+06
[80]	valid_0's l1: 1.58417e+06
[81]	valid_0's l1: 1.58494e+06
[82]	valid_0's l1: 1.58513e+06
[83]	valid_0's l1: 1.58645e+06
[84]	valid_0's l1: 1.58739e+06
[85]	valid_0's l1: 1.58657e+06
[86]	valid_0's l1: 1.58803e+06
[87]	valid_0's l1: 1.58818e+06
[88]	valid_0's l1: 1.58914e+06
[89]	valid_0's l1: 1.58878e+06
[90]	valid_0's l1: 1.58933e+06
[91]	valid_0's l1: 1.58835e+06
[92]	valid_0's l1: 1.5869e+06
[93]	valid_0's l1: 1.58721e+06
[94]	valid_0's l1: 1.58837e+06
[95]	valid_0's l1: 1.58912e+06
[96]	valid_0's l1: 1.58927e+06
[97]	valid_0's l1: 1.58881e+06
[98]	valid_0's l1: 1.59116e+06
Early stopping, best iteration is:
[68]	valid_0's l1: 1.57942e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.893e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58967e+06
[3]	valid_0's l1: 3.32468e+06
[4]	valid_0's l1: 3.09825e+06
[5]	valid_0's l1: 2.89071e+06
[6]	valid_0's l1: 2.80154e+06
[7]	valid_0's l1: 2.71644e+06
[8]	valid_0's l1: 2.56741e+06
[9]	valid_0's l1: 2.43756e+06
[10]	valid_0's l1: 2.32643e+06
[11]	valid_0's l1: 2.23079e+06
[12]	valid_0's l1: 2.18948e+06
[13]	valid_0's l1: 2.10749e+06
[14]	valid_0's l1: 2.08242e+06
[15]	valid_0's l1: 2.01493e+06
[16]	valid_0's l1: 1.95632e+06
[17]	valid_0's l1: 1.90485e+06
[18]	valid_0's l1: 1.86042e+06
[19]	valid_0's l1: 1.82396e+06
[20]	valid_0's l1: 1.79462e+06
[21]	valid_0's l1: 1.76725e+06
[22]	valid_0's l1: 1.7403e+06
[23]	valid_0's l1: 1.71626e+06
[24]	valid_0's l1: 1.69631e+06
[25]	valid_0's l1: 1.67999e+06
[26]	valid_0's l1: 1.66406e+06
[27]	valid_0's l1: 1.65339e+06
[28]	valid_0's l1: 1.64006e+06
[29]	valid_0's l1: 1.63299e+06
[30]	valid_0's l1: 1.63076e+06
[31]	valid_0's l1: 1.6258e+06
[32]	valid_0's l1: 1.62122e+06
[33]	valid_0's l1: 1.616e+06
[34]	valid_0's l1: 1.61383e+06
[35]	valid_0's l1: 1.61383e+06
[36]	valid_0's l1: 1.60584e+06
[37]	valid_0's l1: 1.60486e+06
[38]	valid_0's l1: 1.60448e+06
[39]	valid_0's l1: 1.59697e+06
[40]	valid_0's l1: 1.5953e+06
[41]	valid_0's l1: 1.59587e+06
[42]	valid_0's l1: 1.59189e+06
[43]	valid_0's l1: 1.59228e+06
[44]	valid_0's l1: 1.58958e+06
[45]	valid_0's l1: 1.58835e+06
[46]	valid_0's l1: 1.5905e+06
[47]	valid_0's l1: 1.59163e+06
[48]	valid_0's l1: 1.58945e+06
[49]	valid_0's l1: 1.59093e+06
[50]	valid_0's l1: 1.58741e+06
[51]	valid_0's l1: 1.58842e+06
[52]	valid_0's l1: 1.58895e+06
[53]	valid_0's l1: 1.59036e+06
[54]	valid_0's l1: 1.59301e+06
[55]	valid_0's l1: 1.59183e+06
[56]	valid_0's l1: 1.58957e+06
[57]	valid_0's l1: 1.59206e+06
[58]	valid_0's l1: 1.5917e+06
[59]	valid_0's l1: 1.59371e+06
[60]	valid_0's l1: 1.59457e+06
[61]	valid_0's l1: 1.59512e+06
[62]	valid_0's l1: 1.59525e+06
[63]	valid_0's l1: 1.59274e+06
[64]	valid_0's l1: 1.5912e+06
[65]	valid_0's l1: 1.59183e+06
[66]	valid_0's l1: 1.59296e+06
[67]	valid_0's l1: 1.5923e+06
[68]	valid_0's l1: 1.59439e+06
[69]	valid_0's l1: 1.59513e+06
[70]	valid_0's l1: 1.59526e+06
[71]	valid_0's l1: 1.59688e+06
[72]	valid_0's l1: 1.59705e+06
[73]	valid_0's l1: 1.59793e+06
[74]	valid_0's l1: 1.59769e+06
[75]	valid_0's l1: 1.59656e+06
[76]	valid_0's l1: 1.59516e+06
[77]	valid_0's l1: 1.59735e+06
[78]	valid_0's l1: 1.59631e+06
[79]	valid_0's l1: 1.5967e+06
[80]	valid_0's l1: 1.59598e+06
Early stopping, best iteration is:
[50]	valid_0's l1: 1.58741e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.83364e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.5461e+06
[3]	valid_0's l1: 3.29059e+06
[4]	valid_0's l1: 3.05995e+06
[5]	valid_0's l1: 2.86177e+06
[6]	valid_0's l1: 2.77283e+06
[7]	valid_0's l1: 2.69017e+06
[8]	valid_0's l1: 2.54159e+06
[9]	valid_0's l1: 2.41143e+06
[10]	valid_0's l1: 2.30017e+06
[11]	valid_0's l1: 2.20183e+06
[12]	valid_0's l1: 2.15705e+06
[13]	valid_0's l1: 2.07987e+06
[14]	valid_0's l1: 2.05065e+06
[15]	valid_0's l1: 1.98821e+06
[16]	valid_0's l1: 1.93406e+06
[17]	valid_0's l1: 1.88841e+06
[18]	valid_0's l1: 1.8524e+06
[19]	valid_0's l1: 1.81851e+06
[20]	valid_0's l1: 1.78965e+06
[21]	valid_0's l1: 1.76343e+06
[22]	valid_0's l1: 1.74308e+06
[23]	valid_0's l1: 1.7241e+06
[24]	valid_0's l1: 1.70645e+06
[25]	valid_0's l1: 1.69239e+06
[26]	valid_0's l1: 1.67826e+06
[27]	valid_0's l1: 1.66647e+06
[28]	valid_0's l1: 1.65689e+06
[29]	valid_0's l1: 1.64698e+06
[30]	valid_0's l1: 1.63783e+06
[31]	valid_0's l1: 1.62995e+06
[32]	valid_0's l1: 1.62507e+06
[33]	valid_0's l1: 1.62243e+06
[34]	valid_0's l1: 1.61622e+06
[35]	valid_0's l1: 1.61111e+06
[36]	valid_0's l1: 1.6069e+06
[37]	valid_0's l1: 1.6063e+06
[38]	valid_0's l1: 1.60097e+06
[39]	valid_0's l1: 1.60005e+06
[40]	valid_0's l1: 1.59611e+06
[41]	valid_0's l1: 1.59512e+06
[42]	valid_0's l1: 1.59286e+06
[43]	valid_0's l1: 1.5929e+06
[44]	valid_0's l1: 1.59173e+06
[45]	valid_0's l1: 1.59163e+06
[46]	valid_0's l1: 1.59149e+06
[47]	valid_0's l1: 1.59111e+06
[48]	valid_0's l1: 1.59168e+06
[49]	valid_0's l1: 1.59049e+06
[50]	valid_0's l1: 1.58867e+06
[51]	valid_0's l1: 1.58963e+06
[52]	valid_0's l1: 1.5878e+06
[53]	valid_0's l1: 1.58834e+06
[54]	valid_0's l1: 1.58963e+06
[55]	valid_0's l1: 1.59054e+06
[56]	valid_0's l1: 1.58928e+06
[57]	valid_0's l1: 1.59034e+06
[58]	valid_0's l1: 1.59245e+06
[59]	valid_0's l1: 1.59305e+06
[60]	valid_0's l1: 1.59228e+06
[61]	valid_0's l1: 1.59105e+06
[62]	valid_0's l1: 1.59135e+06
[63]	valid_0's l1: 1.59307e+06
[64]	valid_0's l1: 1.59467e+06
[65]	valid_0's l1: 1.59252e+06
[66]	valid_0's l1: 1.59273e+06
[67]	valid_0's l1: 1.59195e+06
[68]	valid_0's l1: 1.59278e+06
[69]	valid_0's l1: 1.59117e+06
[70]	valid_0's l1: 1.59206e+06
[71]	valid_0's l1: 1.58878e+06
[72]	valid_0's l1: 1.58795e+06
[73]	valid_0's l1: 1.58921e+06
[74]	valid_0's l1: 1.58924e+06
[75]	valid_0's l1: 1.58805e+06
[76]	valid_0's l1: 1.59015e+06
[77]	valid_0's l1: 1.58963e+06
[78]	valid_0's l1: 1.59027e+06
[79]	valid_0's l1: 1.59127e+06
[80]	valid_0's l1: 1.59145e+06
[81]	valid_0's l1: 1.59056e+06
[82]	valid_0's l1: 1.58941e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.5878e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.91572e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.61074e+06
[3]	valid_0's l1: 3.33753e+06
[4]	valid_0's l1: 3.10152e+06
[5]	valid_0's l1: 2.89582e+06
[6]	valid_0's l1: 2.79571e+06
[7]	valid_0's l1: 2.70656e+06
[8]	valid_0's l1: 2.55707e+06
[9]	valid_0's l1: 2.42782e+06
[10]	valid_0's l1: 2.31229e+06
[11]	valid_0's l1: 2.20818e+06
[12]	valid_0's l1: 2.16335e+06
[13]	valid_0's l1: 2.08003e+06
[14]	valid_0's l1: 2.05301e+06
[15]	valid_0's l1: 1.99207e+06
[16]	valid_0's l1: 1.94133e+06
[17]	valid_0's l1: 1.89339e+06
[18]	valid_0's l1: 1.85478e+06
[19]	valid_0's l1: 1.8147e+06
[20]	valid_0's l1: 1.78487e+06
[21]	valid_0's l1: 1.75924e+06
[22]	valid_0's l1: 1.74016e+06
[23]	valid_0's l1: 1.71891e+06
[24]	valid_0's l1: 1.70106e+06
[25]	valid_0's l1: 1.68439e+06
[26]	valid_0's l1: 1.67383e+06
[27]	valid_0's l1: 1.65878e+06
[28]	valid_0's l1: 1.649e+06
[29]	valid_0's l1: 1.63901e+06
[30]	valid_0's l1: 1.62905e+06
[31]	valid_0's l1: 1.62759e+06
[32]	valid_0's l1: 1.61952e+06
[33]	valid_0's l1: 1.61689e+06
[34]	valid_0's l1: 1.61312e+06
[35]	valid_0's l1: 1.60736e+06
[36]	valid_0's l1: 1.60514e+06
[37]	valid_0's l1: 1.60376e+06
[38]	valid_0's l1: 1.60592e+06
[39]	valid_0's l1: 1.60543e+06
[40]	valid_0's l1: 1.59799e+06
[41]	valid_0's l1: 1.59851e+06
[42]	valid_0's l1: 1.59751e+06
[43]	valid_0's l1: 1.59811e+06
[44]	valid_0's l1: 1.59782e+06
[45]	valid_0's l1: 1.59742e+06
[46]	valid_0's l1: 1.59288e+06
[47]	valid_0's l1: 1.59251e+06
[48]	valid_0's l1: 1.59195e+06
[49]	valid_0's l1: 1.58928e+06
[50]	valid_0's l1: 1.59053e+06
[51]	valid_0's l1: 1.59081e+06
[52]	valid_0's l1: 1.59059e+06
[53]	valid_0's l1: 1.59177e+06
[54]	valid_0's l1: 1.59203e+06
[55]	valid_0's l1: 1.59381e+06
[56]	valid_0's l1: 1.59399e+06
[57]	valid_0's l1: 1.59315e+06
[58]	valid_0's l1: 1.59266e+06
[59]	valid_0's l1: 1.59384e+06
[60]	valid_0's l1: 1.59174e+06
[61]	valid_0's l1: 1.58921e+06
[62]	valid_0's l1: 1.58785e+06
[63]	valid_0's l1: 1.58523e+06
[64]	valid_0's l1: 1.58298e+06
[65]	valid_0's l1: 1.58113e+06
[66]	valid_0's l1: 1.58106e+06
[67]	valid_0's l1: 1.58116e+06
[68]	valid_0's l1: 1.57942e+06
[69]	valid_0's l1: 1.58066e+06
[70]	valid_0's l1: 1.58022e+06
[71]	valid_0's l1: 1.5808e+06
[72]	valid_0's l1: 1.58208e+06
[73]	valid_0's l1: 1.58456e+06
[74]	valid_0's l1: 1.58385e+06
[75]	valid_0's l1: 1.58498e+06
[76]	valid_0's l1: 1.58434e+06
[77]	valid_0's l1: 1.58475e+06
[78]	valid_0's l1: 1.58145e+06
[79]	valid_0's l1: 1.58196e+06
[80]	valid_0's l1: 1.58417e+06
[81]	valid_0's l1: 1.58494e+06
[82]	valid_0's l1: 1.58513e+06
[83]	valid_0's l1: 1.58645e+06
[84]	valid_0's l1: 1.58739e+06
[85]	valid_0's l1: 1.58657e+06
[86]	valid_0's l1: 1.58803e+06
[87]	valid_0's l1: 1.58818e+06
[88]	valid_0's l1: 1.58914e+06
[89]	valid_0's l1: 1.58878e+06
[90]	valid_0's l1: 1.58933e+06
[91]	valid_0's l1: 1.58835e+06
[92]	valid_0's l1: 1.5869e+06
[93]	valid_0's l1: 1.58721e+06
[94]	valid_0's l1: 1.58837e+06
[95]	valid_0's l1: 1.58912e+06
[96]	valid_0's l1: 1.58927e+06
[97]	valid_0's l1: 1.58881e+06
[98]	valid_0's l1: 1.59116e+06
Early stopping, best iteration is:
[68]	valid_0's l1: 1.57942e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.893e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58967e+06
[3]	valid_0's l1: 3.32468e+06
[4]	valid_0's l1: 3.09825e+06
[5]	valid_0's l1: 2.89071e+06
[6]	valid_0's l1: 2.80154e+06
[7]	valid_0's l1: 2.71644e+06
[8]	valid_0's l1: 2.56741e+06
[9]	valid_0's l1: 2.43756e+06
[10]	valid_0's l1: 2.32643e+06
[11]	valid_0's l1: 2.23079e+06
[12]	valid_0's l1: 2.18948e+06
[13]	valid_0's l1: 2.10749e+06
[14]	valid_0's l1: 2.08242e+06
[15]	valid_0's l1: 2.01493e+06
[16]	valid_0's l1: 1.95632e+06
[17]	valid_0's l1: 1.90485e+06
[18]	valid_0's l1: 1.86042e+06
[19]	valid_0's l1: 1.82396e+06
[20]	valid_0's l1: 1.79462e+06
[21]	valid_0's l1: 1.76725e+06
[22]	valid_0's l1: 1.7403e+06
[23]	valid_0's l1: 1.71626e+06
[24]	valid_0's l1: 1.69631e+06
[25]	valid_0's l1: 1.67999e+06
[26]	valid_0's l1: 1.66406e+06
[27]	valid_0's l1: 1.65339e+06
[28]	valid_0's l1: 1.64006e+06
[29]	valid_0's l1: 1.63299e+06
[30]	valid_0's l1: 1.63076e+06
[31]	valid_0's l1: 1.6258e+06
[32]	valid_0's l1: 1.62122e+06
[33]	valid_0's l1: 1.616e+06
[34]	valid_0's l1: 1.61383e+06
[35]	valid_0's l1: 1.61383e+06
[36]	valid_0's l1: 1.60584e+06
[37]	valid_0's l1: 1.60486e+06
[38]	valid_0's l1: 1.60448e+06
[39]	valid_0's l1: 1.59697e+06
[40]	valid_0's l1: 1.5953e+06
[41]	valid_0's l1: 1.59587e+06
[42]	valid_0's l1: 1.59189e+06
[43]	valid_0's l1: 1.59228e+06
[44]	valid_0's l1: 1.58958e+06
[45]	valid_0's l1: 1.58835e+06
[46]	valid_0's l1: 1.5905e+06
[47]	valid_0's l1: 1.59163e+06
[48]	valid_0's l1: 1.58945e+06
[49]	valid_0's l1: 1.59093e+06
[50]	valid_0's l1: 1.58741e+06
[51]	valid_0's l1: 1.58842e+06
[52]	valid_0's l1: 1.58895e+06
[53]	valid_0's l1: 1.59036e+06
[54]	valid_0's l1: 1.59301e+06
[55]	valid_0's l1: 1.59183e+06
[56]	valid_0's l1: 1.58957e+06
[57]	valid_0's l1: 1.59206e+06
[58]	valid_0's l1: 1.5917e+06
[59]	valid_0's l1: 1.59371e+06
[60]	valid_0's l1: 1.59457e+06
[61]	valid_0's l1: 1.59512e+06
[62]	valid_0's l1: 1.59525e+06
[63]	valid_0's l1: 1.59274e+06
[64]	valid_0's l1: 1.5912e+06
[65]	valid_0's l1: 1.59183e+06
[66]	valid_0's l1: 1.59296e+06
[67]	valid_0's l1: 1.5923e+06
[68]	valid_0's l1: 1.59439e+06
[69]	valid_0's l1: 1.59513e+06
[70]	valid_0's l1: 1.59526e+06
[71]	valid_0's l1: 1.59688e+06
[72]	valid_0's l1: 1.59705e+06
[73]	valid_0's l1: 1.59793e+06
[74]	valid_0's l1: 1.59769e+06
[75]	valid_0's l1: 1.59656e+06
[76]	valid_0's l1: 1.59516e+06
[77]	valid_0's l1: 1.59735e+06
[78]	valid_0's l1: 1.59631e+06
[79]	valid_0's l1: 1.5967e+06
[80]	valid_0's l1: 1.59598e+06
Early stopping, best iteration is:
[50]	valid_0's l1: 1.58741e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.83364e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.5461e+06
[3]	valid_0's l1: 3.29059e+06
[4]	valid_0's l1: 3.05995e+06
[5]	valid_0's l1: 2.86177e+06
[6]	valid_0's l1: 2.77283e+06
[7]	valid_0's l1: 2.69017e+06
[8]	valid_0's l1: 2.54159e+06
[9]	valid_0's l1: 2.41143e+06
[10]	valid_0's l1: 2.30017e+06
[11]	valid_0's l1: 2.20183e+06
[12]	valid_0's l1: 2.15705e+06
[13]	valid_0's l1: 2.07987e+06
[14]	valid_0's l1: 2.05065e+06
[15]	valid_0's l1: 1.98821e+06
[16]	valid_0's l1: 1.93406e+06
[17]	valid_0's l1: 1.88841e+06
[18]	valid_0's l1: 1.8524e+06
[19]	valid_0's l1: 1.81851e+06
[20]	valid_0's l1: 1.78965e+06
[21]	valid_0's l1: 1.76343e+06
[22]	valid_0's l1: 1.74308e+06
[23]	valid_0's l1: 1.7241e+06
[24]	valid_0's l1: 1.70645e+06
[25]	valid_0's l1: 1.69239e+06
[26]	valid_0's l1: 1.67826e+06
[27]	valid_0's l1: 1.66647e+06
[28]	valid_0's l1: 1.65689e+06
[29]	valid_0's l1: 1.64698e+06
[30]	valid_0's l1: 1.63783e+06
[31]	valid_0's l1: 1.62995e+06
[32]	valid_0's l1: 1.62507e+06
[33]	valid_0's l1: 1.62243e+06
[34]	valid_0's l1: 1.61622e+06
[35]	valid_0's l1: 1.61111e+06
[36]	valid_0's l1: 1.6069e+06
[37]	valid_0's l1: 1.6063e+06
[38]	valid_0's l1: 1.60097e+06
[39]	valid_0's l1: 1.60005e+06
[40]	valid_0's l1: 1.59611e+06
[41]	valid_0's l1: 1.59512e+06
[42]	valid_0's l1: 1.59286e+06
[43]	valid_0's l1: 1.5929e+06
[44]	valid_0's l1: 1.59173e+06
[45]	valid_0's l1: 1.59163e+06
[46]	valid_0's l1: 1.59149e+06
[47]	valid_0's l1: 1.59111e+06
[48]	valid_0's l1: 1.59168e+06
[49]	valid_0's l1: 1.59049e+06
[50]	valid_0's l1: 1.58867e+06
[51]	valid_0's l1: 1.58963e+06
[52]	valid_0's l1: 1.5878e+06
[53]	valid_0's l1: 1.58834e+06
[54]	valid_0's l1: 1.58963e+06
[55]	valid_0's l1: 1.59054e+06
[56]	valid_0's l1: 1.58928e+06
[57]	valid_0's l1: 1.59034e+06
[58]	valid_0's l1: 1.59245e+06
[59]	valid_0's l1: 1.59305e+06
[60]	valid_0's l1: 1.59228e+06
[61]	valid_0's l1: 1.59105e+06
[62]	valid_0's l1: 1.59135e+06
[63]	valid_0's l1: 1.59307e+06
[64]	valid_0's l1: 1.59467e+06
[65]	valid_0's l1: 1.59252e+06
[66]	valid_0's l1: 1.59273e+06
[67]	valid_0's l1: 1.59195e+06
[68]	valid_0's l1: 1.59278e+06
[69]	valid_0's l1: 1.59117e+06
[70]	valid_0's l1: 1.59206e+06
[71]	valid_0's l1: 1.58878e+06
[72]	valid_0's l1: 1.58795e+06
[73]	valid_0's l1: 1.58921e+06
[74]	valid_0's l1: 1.58924e+06
[75]	valid_0's l1: 1.58805e+06
[76]	valid_0's l1: 1.59015e+06
[77]	valid_0's l1: 1.58963e+06
[78]	valid_0's l1: 1.59027e+06
[79]	valid_0's l1: 1.59127e+06
[80]	valid_0's l1: 1.59145e+06
[81]	valid_0's l1: 1.59056e+06
[82]	valid_0's l1: 1.58941e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.5878e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.91572e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.61074e+06
[3]	valid_0's l1: 3.33753e+06
[4]	valid_0's l1: 3.10152e+06
[5]	valid_0's l1: 2.89582e+06
[6]	valid_0's l1: 2.79571e+06
[7]	valid_0's l1: 2.70656e+06
[8]	valid_0's l1: 2.55707e+06
[9]	valid_0's l1: 2.42782e+06
[10]	valid_0's l1: 2.31229e+06
[11]	valid_0's l1: 2.20818e+06
[12]	valid_0's l1: 2.16335e+06
[13]	valid_0's l1: 2.08003e+06
[14]	valid_0's l1: 2.05301e+06
[15]	valid_0's l1: 1.99207e+06
[16]	valid_0's l1: 1.94133e+06
[17]	valid_0's l1: 1.89339e+06
[18]	valid_0's l1: 1.85478e+06
[19]	valid_0's l1: 1.8147e+06
[20]	valid_0's l1: 1.78487e+06
[21]	valid_0's l1: 1.75924e+06
[22]	valid_0's l1: 1.74016e+06
[23]	valid_0's l1: 1.71891e+06
[24]	valid_0's l1: 1.70106e+06
[25]	valid_0's l1: 1.68439e+06
[26]	valid_0's l1: 1.67383e+06
[27]	valid_0's l1: 1.65878e+06
[28]	valid_0's l1: 1.649e+06
[29]	valid_0's l1: 1.63901e+06
[30]	valid_0's l1: 1.62905e+06
[31]	valid_0's l1: 1.62759e+06
[32]	valid_0's l1: 1.61952e+06
[33]	valid_0's l1: 1.61689e+06
[34]	valid_0's l1: 1.61312e+06
[35]	valid_0's l1: 1.60736e+06
[36]	valid_0's l1: 1.60514e+06
[37]	valid_0's l1: 1.60376e+06
[38]	valid_0's l1: 1.60592e+06
[39]	valid_0's l1: 1.60543e+06
[40]	valid_0's l1: 1.59799e+06
[41]	valid_0's l1: 1.59851e+06
[42]	valid_0's l1: 1.59751e+06
[43]	valid_0's l1: 1.59811e+06
[44]	valid_0's l1: 1.59782e+06
[45]	valid_0's l1: 1.59742e+06
[46]	valid_0's l1: 1.59288e+06
[47]	valid_0's l1: 1.59251e+06
[48]	valid_0's l1: 1.59195e+06
[49]	valid_0's l1: 1.58928e+06
[50]	valid_0's l1: 1.59053e+06
[51]	valid_0's l1: 1.59081e+06
[52]	valid_0's l1: 1.59059e+06
[53]	valid_0's l1: 1.59177e+06
[54]	valid_0's l1: 1.59203e+06
[55]	valid_0's l1: 1.59381e+06
[56]	valid_0's l1: 1.59399e+06
[57]	valid_0's l1: 1.59315e+06
[58]	valid_0's l1: 1.59266e+06
[59]	valid_0's l1: 1.59384e+06
[60]	valid_0's l1: 1.59174e+06
[61]	valid_0's l1: 1.58921e+06
[62]	valid_0's l1: 1.58785e+06
[63]	valid_0's l1: 1.58523e+06
[64]	valid_0's l1: 1.58298e+06
[65]	valid_0's l1: 1.58113e+06
[66]	valid_0's l1: 1.58106e+06
[67]	valid_0's l1: 1.58116e+06
[68]	valid_0's l1: 1.57942e+06
[69]	valid_0's l1: 1.58066e+06
[70]	valid_0's l1: 1.58022e+06
[71]	valid_0's l1: 1.5808e+06
[72]	valid_0's l1: 1.58208e+06
[73]	valid_0's l1: 1.58456e+06
[74]	valid_0's l1: 1.58385e+06
[75]	valid_0's l1: 1.58498e+06
[76]	valid_0's l1: 1.58434e+06
[77]	valid_0's l1: 1.58475e+06
[78]	valid_0's l1: 1.58145e+06
[79]	valid_0's l1: 1.58196e+06
[80]	valid_0's l1: 1.58417e+06
[81]	valid_0's l1: 1.58494e+06
[82]	valid_0's l1: 1.58513e+06
[83]	valid_0's l1: 1.58645e+06
[84]	valid_0's l1: 1.58739e+06
[85]	valid_0's l1: 1.58657e+06
[86]	valid_0's l1: 1.58803e+06
[87]	valid_0's l1: 1.58818e+06
[88]	valid_0's l1: 1.58914e+06
[89]	valid_0's l1: 1.58878e+06
[90]	valid_0's l1: 1.58933e+06
[91]	valid_0's l1: 1.58835e+06
[92]	valid_0's l1: 1.5869e+06
[93]	valid_0's l1: 1.58721e+06
[94]	valid_0's l1: 1.58837e+06
[95]	valid_0's l1: 1.58912e+06
[96]	valid_0's l1: 1.58927e+06
[97]	valid_0's l1: 1.58881e+06
[98]	valid_0's l1: 1.59116e+06
Early stopping, best iteration is:
[68]	valid_0's l1: 1.57942e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.893e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58967e+06
[3]	valid_0's l1: 3.32468e+06
[4]	valid_0's l1: 3.09825e+06
[5]	valid_0's l1: 2.89071e+06
[6]	valid_0's l1: 2.80154e+06
[7]	valid_0's l1: 2.71644e+06
[8]	valid_0's l1: 2.56741e+06
[9]	valid_0's l1: 2.43756e+06
[10]	valid_0's l1: 2.32643e+06
[11]	valid_0's l1: 2.23079e+06
[12]	valid_0's l1: 2.18948e+06
[13]	valid_0's l1: 2.10749e+06
[14]	valid_0's l1: 2.08242e+06
[15]	valid_0's l1: 2.01493e+06
[16]	valid_0's l1: 1.95632e+06
[17]	valid_0's l1: 1.90485e+06
[18]	valid_0's l1: 1.86042e+06
[19]	valid_0's l1: 1.82396e+06
[20]	valid_0's l1: 1.79462e+06
[21]	valid_0's l1: 1.76725e+06
[22]	valid_0's l1: 1.7403e+06
[23]	valid_0's l1: 1.71626e+06
[24]	valid_0's l1: 1.69631e+06
[25]	valid_0's l1: 1.67999e+06
[26]	valid_0's l1: 1.66406e+06
[27]	valid_0's l1: 1.65339e+06
[28]	valid_0's l1: 1.64006e+06
[29]	valid_0's l1: 1.63299e+06
[30]	valid_0's l1: 1.63076e+06
[31]	valid_0's l1: 1.6258e+06
[32]	valid_0's l1: 1.62122e+06
[33]	valid_0's l1: 1.616e+06
[34]	valid_0's l1: 1.61383e+06
[35]	valid_0's l1: 1.61383e+06
[36]	valid_0's l1: 1.60584e+06
[37]	valid_0's l1: 1.60486e+06
[38]	valid_0's l1: 1.60448e+06
[39]	valid_0's l1: 1.59697e+06
[40]	valid_0's l1: 1.5953e+06
[41]	valid_0's l1: 1.59587e+06
[42]	valid_0's l1: 1.59189e+06
[43]	valid_0's l1: 1.59228e+06
[44]	valid_0's l1: 1.58958e+06
[45]	valid_0's l1: 1.58835e+06
[46]	valid_0's l1: 1.5905e+06
[47]	valid_0's l1: 1.59163e+06
[48]	valid_0's l1: 1.58945e+06
[49]	valid_0's l1: 1.59093e+06
[50]	valid_0's l1: 1.58741e+06
[51]	valid_0's l1: 1.58842e+06
[52]	valid_0's l1: 1.58895e+06
[53]	valid_0's l1: 1.59036e+06
[54]	valid_0's l1: 1.59301e+06
[55]	valid_0's l1: 1.59183e+06
[56]	valid_0's l1: 1.58957e+06
[57]	valid_0's l1: 1.59206e+06
[58]	valid_0's l1: 1.5917e+06
[59]	valid_0's l1: 1.59371e+06
[60]	valid_0's l1: 1.59457e+06
[61]	valid_0's l1: 1.59512e+06
[62]	valid_0's l1: 1.59525e+06
[63]	valid_0's l1: 1.59274e+06
[64]	valid_0's l1: 1.5912e+06
[65]	valid_0's l1: 1.59183e+06
[66]	valid_0's l1: 1.59296e+06
[67]	valid_0's l1: 1.5923e+06
[68]	valid_0's l1: 1.59439e+06
[69]	valid_0's l1: 1.59513e+06
[70]	valid_0's l1: 1.59526e+06
[71]	valid_0's l1: 1.59688e+06
[72]	valid_0's l1: 1.59705e+06
[73]	valid_0's l1: 1.59793e+06
[74]	valid_0's l1: 1.59769e+06
[75]	valid_0's l1: 1.59656e+06
[76]	valid_0's l1: 1.59516e+06
[77]	valid_0's l1: 1.59735e+06
[78]	valid_0's l1: 1.59631e+06
[79]	valid_0's l1: 1.5967e+06
[80]	valid_0's l1: 1.59598e+06
Early stopping, best iteration is:
[50]	valid_0's l1: 1.58741e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.83364e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.5461e+06
[3]	valid_0's l1: 3.29059e+06
[4]	valid_0's l1: 3.05995e+06
[5]	valid_0's l1: 2.86177e+06
[6]	valid_0's l1: 2.77283e+06
[7]	valid_0's l1: 2.69017e+06
[8]	valid_0's l1: 2.54159e+06
[9]	valid_0's l1: 2.41143e+06
[10]	valid_0's l1: 2.30017e+06
[11]	valid_0's l1: 2.20183e+06
[12]	valid_0's l1: 2.15705e+06
[13]	valid_0's l1: 2.07987e+06
[14]	valid_0's l1: 2.05065e+06
[15]	valid_0's l1: 1.98821e+06
[16]	valid_0's l1: 1.93406e+06
[17]	valid_0's l1: 1.88841e+06
[18]	valid_0's l1: 1.8524e+06
[19]	valid_0's l1: 1.81851e+06
[20]	valid_0's l1: 1.78965e+06
[21]	valid_0's l1: 1.76343e+06
[22]	valid_0's l1: 1.74308e+06
[23]	valid_0's l1: 1.7241e+06
[24]	valid_0's l1: 1.70645e+06
[25]	valid_0's l1: 1.69239e+06
[26]	valid_0's l1: 1.67826e+06
[27]	valid_0's l1: 1.66647e+06
[28]	valid_0's l1: 1.65689e+06
[29]	valid_0's l1: 1.64698e+06
[30]	valid_0's l1: 1.63783e+06
[31]	valid_0's l1: 1.62995e+06
[32]	valid_0's l1: 1.62507e+06
[33]	valid_0's l1: 1.62243e+06
[34]	valid_0's l1: 1.61622e+06
[35]	valid_0's l1: 1.61111e+06
[36]	valid_0's l1: 1.6069e+06
[37]	valid_0's l1: 1.6063e+06
[38]	valid_0's l1: 1.60097e+06
[39]	valid_0's l1: 1.60005e+06
[40]	valid_0's l1: 1.59611e+06
[41]	valid_0's l1: 1.59512e+06
[42]	valid_0's l1: 1.59286e+06
[43]	valid_0's l1: 1.5929e+06
[44]	valid_0's l1: 1.59173e+06
[45]	valid_0's l1: 1.59163e+06
[46]	valid_0's l1: 1.59149e+06
[47]	valid_0's l1: 1.59111e+06
[48]	valid_0's l1: 1.59168e+06
[49]	valid_0's l1: 1.59049e+06
[50]	valid_0's l1: 1.58867e+06
[51]	valid_0's l1: 1.58963e+06
[52]	valid_0's l1: 1.5878e+06
[53]	valid_0's l1: 1.58834e+06
[54]	valid_0's l1: 1.58963e+06
[55]	valid_0's l1: 1.59054e+06
[56]	valid_0's l1: 1.58928e+06
[57]	valid_0's l1: 1.59034e+06
[58]	valid_0's l1: 1.59245e+06
[59]	valid_0's l1: 1.59305e+06
[60]	valid_0's l1: 1.59228e+06
[61]	valid_0's l1: 1.59105e+06
[62]	valid_0's l1: 1.59135e+06
[63]	valid_0's l1: 1.59307e+06
[64]	valid_0's l1: 1.59467e+06
[65]	valid_0's l1: 1.59252e+06
[66]	valid_0's l1: 1.59273e+06
[67]	valid_0's l1: 1.59195e+06
[68]	valid_0's l1: 1.59278e+06
[69]	valid_0's l1: 1.59117e+06
[70]	valid_0's l1: 1.59206e+06
[71]	valid_0's l1: 1.58878e+06
[72]	valid_0's l1: 1.58795e+06
[73]	valid_0's l1: 1.58921e+06
[74]	valid_0's l1: 1.58924e+06
[75]	valid_0's l1: 1.58805e+06
[76]	valid_0's l1: 1.59015e+06
[77]	valid_0's l1: 1.58963e+06
[78]	valid_0's l1: 1.59027e+06
[79]	valid_0's l1: 1.59127e+06
[80]	valid_0's l1: 1.59145e+06
[81]	valid_0's l1: 1.59056e+06
[82]	valid_0's l1: 1.58941e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.5878e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.91572e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.61074e+06
[3]	valid_0's l1: 3.33753e+06
[4]	valid_0's l1: 3.10152e+06
[5]	valid_0's l1: 2.89582e+06
[6]	valid_0's l1: 2.79571e+06
[7]	valid_0's l1: 2.70656e+06
[8]	valid_0's l1: 2.55707e+06
[9]	valid_0's l1: 2.42782e+06
[10]	valid_0's l1: 2.31229e+06
[11]	valid_0's l1: 2.20818e+06
[12]	valid_0's l1: 2.16335e+06
[13]	valid_0's l1: 2.08003e+06
[14]	valid_0's l1: 2.05301e+06
[15]	valid_0's l1: 1.99207e+06
[16]	valid_0's l1: 1.94133e+06
[17]	valid_0's l1: 1.89339e+06
[18]	valid_0's l1: 1.85478e+06
[19]	valid_0's l1: 1.8147e+06
[20]	valid_0's l1: 1.78487e+06
[21]	valid_0's l1: 1.75924e+06
[22]	valid_0's l1: 1.74016e+06
[23]	valid_0's l1: 1.71891e+06
[24]	valid_0's l1: 1.70106e+06
[25]	valid_0's l1: 1.68439e+06
[26]	valid_0's l1: 1.67383e+06
[27]	valid_0's l1: 1.65878e+06
[28]	valid_0's l1: 1.649e+06
[29]	valid_0's l1: 1.63901e+06
[30]	valid_0's l1: 1.62905e+06
[31]	valid_0's l1: 1.62759e+06
[32]	valid_0's l1: 1.61952e+06
[33]	valid_0's l1: 1.61689e+06
[34]	valid_0's l1: 1.61312e+06
[35]	valid_0's l1: 1.60736e+06
[36]	valid_0's l1: 1.60514e+06
[37]	valid_0's l1: 1.60376e+06
[38]	valid_0's l1: 1.60592e+06
[39]	valid_0's l1: 1.60543e+06
[40]	valid_0's l1: 1.59799e+06
[41]	valid_0's l1: 1.59851e+06
[42]	valid_0's l1: 1.59751e+06
[43]	valid_0's l1: 1.59811e+06
[44]	valid_0's l1: 1.59782e+06
[45]	valid_0's l1: 1.59742e+06
[46]	valid_0's l1: 1.59288e+06
[47]	valid_0's l1: 1.59251e+06
[48]	valid_0's l1: 1.59195e+06
[49]	valid_0's l1: 1.58928e+06
[50]	valid_0's l1: 1.59053e+06
[51]	valid_0's l1: 1.59081e+06
[52]	valid_0's l1: 1.59059e+06
[53]	valid_0's l1: 1.59177e+06
[54]	valid_0's l1: 1.59203e+06
[55]	valid_0's l1: 1.59381e+06
[56]	valid_0's l1: 1.59399e+06
[57]	valid_0's l1: 1.59315e+06
[58]	valid_0's l1: 1.59266e+06
[59]	valid_0's l1: 1.59384e+06
[60]	valid_0's l1: 1.59174e+06
[61]	valid_0's l1: 1.58921e+06
[62]	valid_0's l1: 1.58785e+06
[63]	valid_0's l1: 1.58523e+06
[64]	valid_0's l1: 1.58298e+06
[65]	valid_0's l1: 1.58113e+06
[66]	valid_0's l1: 1.58106e+06
[67]	valid_0's l1: 1.58116e+06
[68]	valid_0's l1: 1.57942e+06
[69]	valid_0's l1: 1.58066e+06
[70]	valid_0's l1: 1.58022e+06
[71]	valid_0's l1: 1.5808e+06
[72]	valid_0's l1: 1.58208e+06
[73]	valid_0's l1: 1.58456e+06
[74]	valid_0's l1: 1.58385e+06
[75]	valid_0's l1: 1.58498e+06
[76]	valid_0's l1: 1.58434e+06
[77]	valid_0's l1: 1.58475e+06
[78]	valid_0's l1: 1.58145e+06
[79]	valid_0's l1: 1.58196e+06
[80]	valid_0's l1: 1.58417e+06
[81]	valid_0's l1: 1.58494e+06
[82]	valid_0's l1: 1.58513e+06
[83]	valid_0's l1: 1.58645e+06
[84]	valid_0's l1: 1.58739e+06
[85]	valid_0's l1: 1.58657e+06
[86]	valid_0's l1: 1.58803e+06
[87]	valid_0's l1: 1.58818e+06
[88]	valid_0's l1: 1.58914e+06
[89]	valid_0's l1: 1.58878e+06
[90]	valid_0's l1: 1.58933e+06
[91]	valid_0's l1: 1.58835e+06
[92]	valid_0's l1: 1.5869e+06
[93]	valid_0's l1: 1.58721e+06
[94]	valid_0's l1: 1.58837e+06
[95]	valid_0's l1: 1.58912e+06
[96]	valid_0's l1: 1.58927e+06
[97]	valid_0's l1: 1.58881e+06
[98]	valid_0's l1: 1.59116e+06
Early stopping, best iteration is:
[68]	valid_0's l1: 1.57942e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.893e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58967e+06
[3]	valid_0's l1: 3.32468e+06
[4]	valid_0's l1: 3.09825e+06
[5]	valid_0's l1: 2.89071e+06
[6]	valid_0's l1: 2.80154e+06
[7]	valid_0's l1: 2.71644e+06
[8]	valid_0's l1: 2.56741e+06
[9]	valid_0's l1: 2.43756e+06
[10]	valid_0's l1: 2.32643e+06
[11]	valid_0's l1: 2.23079e+06
[12]	valid_0's l1: 2.18948e+06
[13]	valid_0's l1: 2.10749e+06
[14]	valid_0's l1: 2.08242e+06
[15]	valid_0's l1: 2.01493e+06
[16]	valid_0's l1: 1.95632e+06
[17]	valid_0's l1: 1.90485e+06
[18]	valid_0's l1: 1.86042e+06
[19]	valid_0's l1: 1.82396e+06
[20]	valid_0's l1: 1.79462e+06
[21]	valid_0's l1: 1.76725e+06
[22]	valid_0's l1: 1.7403e+06
[23]	valid_0's l1: 1.71626e+06
[24]	valid_0's l1: 1.69631e+06
[25]	valid_0's l1: 1.67999e+06
[26]	valid_0's l1: 1.66406e+06
[27]	valid_0's l1: 1.65339e+06
[28]	valid_0's l1: 1.64006e+06
[29]	valid_0's l1: 1.63299e+06
[30]	valid_0's l1: 1.63076e+06
[31]	valid_0's l1: 1.6258e+06
[32]	valid_0's l1: 1.62122e+06
[33]	valid_0's l1: 1.616e+06
[34]	valid_0's l1: 1.61383e+06
[35]	valid_0's l1: 1.61383e+06
[36]	valid_0's l1: 1.60584e+06
[37]	valid_0's l1: 1.60486e+06
[38]	valid_0's l1: 1.60448e+06
[39]	valid_0's l1: 1.59697e+06
[40]	valid_0's l1: 1.5953e+06
[41]	valid_0's l1: 1.59587e+06
[42]	valid_0's l1: 1.59189e+06
[43]	valid_0's l1: 1.59228e+06
[44]	valid_0's l1: 1.58958e+06
[45]	valid_0's l1: 1.58835e+06
[46]	valid_0's l1: 1.5905e+06
[47]	valid_0's l1: 1.59163e+06
[48]	valid_0's l1: 1.58945e+06
[49]	valid_0's l1: 1.59093e+06
[50]	valid_0's l1: 1.58741e+06
[51]	valid_0's l1: 1.58842e+06
[52]	valid_0's l1: 1.58895e+06
[53]	valid_0's l1: 1.59036e+06
[54]	valid_0's l1: 1.59301e+06
[55]	valid_0's l1: 1.59183e+06
[56]	valid_0's l1: 1.58957e+06
[57]	valid_0's l1: 1.59206e+06
[58]	valid_0's l1: 1.5917e+06
[59]	valid_0's l1: 1.59371e+06
[60]	valid_0's l1: 1.59457e+06
[61]	valid_0's l1: 1.59512e+06
[62]	valid_0's l1: 1.59525e+06
[63]	valid_0's l1: 1.59274e+06
[64]	valid_0's l1: 1.5912e+06
[65]	valid_0's l1: 1.59183e+06
[66]	valid_0's l1: 1.59296e+06
[67]	valid_0's l1: 1.5923e+06
[68]	valid_0's l1: 1.59439e+06
[69]	valid_0's l1: 1.59513e+06
[70]	valid_0's l1: 1.59526e+06
[71]	valid_0's l1: 1.59688e+06
[72]	valid_0's l1: 1.59705e+06
[73]	valid_0's l1: 1.59793e+06
[74]	valid_0's l1: 1.59769e+06
[75]	valid_0's l1: 1.59656e+06
[76]	valid_0's l1: 1.59516e+06
[77]	valid_0's l1: 1.59735e+06
[78]	valid_0's l1: 1.59631e+06
[79]	valid_0's l1: 1.5967e+06
[80]	valid_0's l1: 1.59598e+06
Early stopping, best iteration is:
[50]	valid_0's l1: 1.58741e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.83364e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.5461e+06
[3]	valid_0's l1: 3.29059e+06
[4]	valid_0's l1: 3.05995e+06
[5]	valid_0's l1: 2.86177e+06
[6]	valid_0's l1: 2.77283e+06
[7]	valid_0's l1: 2.69017e+06
[8]	valid_0's l1: 2.54159e+06
[9]	valid_0's l1: 2.41143e+06
[10]	valid_0's l1: 2.30017e+06
[11]	valid_0's l1: 2.20183e+06
[12]	valid_0's l1: 2.15705e+06
[13]	valid_0's l1: 2.07987e+06
[14]	valid_0's l1: 2.05065e+06
[15]	valid_0's l1: 1.98821e+06
[16]	valid_0's l1: 1.93406e+06
[17]	valid_0's l1: 1.88841e+06
[18]	valid_0's l1: 1.8524e+06
[19]	valid_0's l1: 1.81851e+06
[20]	valid_0's l1: 1.78965e+06
[21]	valid_0's l1: 1.76343e+06
[22]	valid_0's l1: 1.74308e+06
[23]	valid_0's l1: 1.7241e+06
[24]	valid_0's l1: 1.70645e+06
[25]	valid_0's l1: 1.69239e+06
[26]	valid_0's l1: 1.67826e+06
[27]	valid_0's l1: 1.66647e+06
[28]	valid_0's l1: 1.65689e+06
[29]	valid_0's l1: 1.64698e+06
[30]	valid_0's l1: 1.63783e+06
[31]	valid_0's l1: 1.62995e+06
[32]	valid_0's l1: 1.62507e+06
[33]	valid_0's l1: 1.62243e+06
[34]	valid_0's l1: 1.61622e+06
[35]	valid_0's l1: 1.61111e+06
[36]	valid_0's l1: 1.6069e+06
[37]	valid_0's l1: 1.6063e+06
[38]	valid_0's l1: 1.60097e+06
[39]	valid_0's l1: 1.60005e+06
[40]	valid_0's l1: 1.59611e+06
[41]	valid_0's l1: 1.59512e+06
[42]	valid_0's l1: 1.59286e+06
[43]	valid_0's l1: 1.5929e+06
[44]	valid_0's l1: 1.59173e+06
[45]	valid_0's l1: 1.59163e+06
[46]	valid_0's l1: 1.59149e+06
[47]	valid_0's l1: 1.59111e+06
[48]	valid_0's l1: 1.59168e+06
[49]	valid_0's l1: 1.59049e+06
[50]	valid_0's l1: 1.58867e+06
[51]	valid_0's l1: 1.58963e+06
[52]	valid_0's l1: 1.5878e+06
[53]	valid_0's l1: 1.58834e+06
[54]	valid_0's l1: 1.58963e+06
[55]	valid_0's l1: 1.59054e+06
[56]	valid_0's l1: 1.58928e+06
[57]	valid_0's l1: 1.59034e+06
[58]	valid_0's l1: 1.59245e+06
[59]	valid_0's l1: 1.59305e+06
[60]	valid_0's l1: 1.59228e+06
[61]	valid_0's l1: 1.59105e+06
[62]	valid_0's l1: 1.59135e+06
[63]	valid_0's l1: 1.59307e+06
[64]	valid_0's l1: 1.59467e+06
[65]	valid_0's l1: 1.59252e+06
[66]	valid_0's l1: 1.59273e+06
[67]	valid_0's l1: 1.59195e+06
[68]	valid_0's l1: 1.59278e+06
[69]	valid_0's l1: 1.59117e+06
[70]	valid_0's l1: 1.59206e+06
[71]	valid_0's l1: 1.58878e+06
[72]	valid_0's l1: 1.58795e+06
[73]	valid_0's l1: 1.58921e+06
[74]	valid_0's l1: 1.58924e+06
[75]	valid_0's l1: 1.58805e+06
[76]	valid_0's l1: 1.59015e+06
[77]	valid_0's l1: 1.58963e+06
[78]	valid_0's l1: 1.59027e+06
[79]	valid_0's l1: 1.59127e+06
[80]	valid_0's l1: 1.59145e+06
[81]	valid_0's l1: 1.59056e+06
[82]	valid_0's l1: 1.58941e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.5878e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.91572e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.61074e+06
[3]	valid_0's l1: 3.33753e+06
[4]	valid_0's l1: 3.10152e+06
[5]	valid_0's l1: 2.89582e+06
[6]	valid_0's l1: 2.79571e+06
[7]	valid_0's l1: 2.70656e+06
[8]	valid_0's l1: 2.55707e+06
[9]	valid_0's l1: 2.42782e+06
[10]	valid_0's l1: 2.31229e+06
[11]	valid_0's l1: 2.20818e+06
[12]	valid_0's l1: 2.16335e+06
[13]	valid_0's l1: 2.08003e+06
[14]	valid_0's l1: 2.05301e+06
[15]	valid_0's l1: 1.99207e+06
[16]	valid_0's l1: 1.94133e+06
[17]	valid_0's l1: 1.89339e+06
[18]	valid_0's l1: 1.85478e+06
[19]	valid_0's l1: 1.8147e+06
[20]	valid_0's l1: 1.78487e+06
[21]	valid_0's l1: 1.75924e+06
[22]	valid_0's l1: 1.74016e+06
[23]	valid_0's l1: 1.71891e+06
[24]	valid_0's l1: 1.70106e+06
[25]	valid_0's l1: 1.68439e+06
[26]	valid_0's l1: 1.67383e+06
[27]	valid_0's l1: 1.65878e+06
[28]	valid_0's l1: 1.649e+06
[29]	valid_0's l1: 1.63901e+06
[30]	valid_0's l1: 1.62905e+06
[31]	valid_0's l1: 1.62759e+06
[32]	valid_0's l1: 1.61952e+06
[33]	valid_0's l1: 1.61689e+06
[34]	valid_0's l1: 1.61312e+06
[35]	valid_0's l1: 1.60736e+06
[36]	valid_0's l1: 1.60514e+06
[37]	valid_0's l1: 1.60376e+06
[38]	valid_0's l1: 1.60592e+06
[39]	valid_0's l1: 1.60543e+06
[40]	valid_0's l1: 1.59799e+06
[41]	valid_0's l1: 1.59851e+06
[42]	valid_0's l1: 1.59751e+06
[43]	valid_0's l1: 1.59811e+06
[44]	valid_0's l1: 1.59782e+06
[45]	valid_0's l1: 1.59742e+06
[46]	valid_0's l1: 1.59288e+06
[47]	valid_0's l1: 1.59251e+06
[48]	valid_0's l1: 1.59195e+06
[49]	valid_0's l1: 1.58928e+06
[50]	valid_0's l1: 1.59053e+06
[51]	valid_0's l1: 1.59081e+06
[52]	valid_0's l1: 1.59059e+06
[53]	valid_0's l1: 1.59177e+06
[54]	valid_0's l1: 1.59203e+06
[55]	valid_0's l1: 1.59381e+06
[56]	valid_0's l1: 1.59399e+06
[57]	valid_0's l1: 1.59315e+06
[58]	valid_0's l1: 1.59266e+06
[59]	valid_0's l1: 1.59384e+06
[60]	valid_0's l1: 1.59174e+06
[61]	valid_0's l1: 1.58921e+06
[62]	valid_0's l1: 1.58785e+06
[63]	valid_0's l1: 1.58523e+06
[64]	valid_0's l1: 1.58298e+06
[65]	valid_0's l1: 1.58113e+06
[66]	valid_0's l1: 1.58106e+06
[67]	valid_0's l1: 1.58116e+06
[68]	valid_0's l1: 1.57942e+06
[69]	valid_0's l1: 1.58066e+06
[70]	valid_0's l1: 1.58022e+06
[71]	valid_0's l1: 1.5808e+06
[72]	valid_0's l1: 1.58208e+06
[73]	valid_0's l1: 1.58456e+06
[74]	valid_0's l1: 1.58385e+06
[75]	valid_0's l1: 1.58498e+06
[76]	valid_0's l1: 1.58434e+06
[77]	valid_0's l1: 1.58475e+06
[78]	valid_0's l1: 1.58145e+06
[79]	valid_0's l1: 1.58196e+06
[80]	valid_0's l1: 1.58417e+06
[81]	valid_0's l1: 1.58494e+06
[82]	valid_0's l1: 1.58513e+06
[83]	valid_0's l1: 1.58645e+06
[84]	valid_0's l1: 1.58739e+06
[85]	valid_0's l1: 1.58657e+06
[86]	valid_0's l1: 1.58803e+06
[87]	valid_0's l1: 1.58818e+06
[88]	valid_0's l1: 1.58914e+06
[89]	valid_0's l1: 1.58878e+06
[90]	valid_0's l1: 1.58933e+06
[91]	valid_0's l1: 1.58835e+06
[92]	valid_0's l1: 1.5869e+06
[93]	valid_0's l1: 1.58721e+06
[94]	valid_0's l1: 1.58837e+06
[95]	valid_0's l1: 1.58912e+06
[96]	valid_0's l1: 1.58927e+06
[97]	valid_0's l1: 1.58881e+06
[98]	valid_0's l1: 1.59116e+06
Early stopping, best iteration is:
[68]	valid_0's l1: 1.57942e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.893e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.58967e+06
[3]	valid_0's l1: 3.32468e+06
[4]	valid_0's l1: 3.09825e+06
[5]	valid_0's l1: 2.89071e+06
[6]	valid_0's l1: 2.80154e+06
[7]	valid_0's l1: 2.71644e+06
[8]	valid_0's l1: 2.56741e+06
[9]	valid_0's l1: 2.43756e+06
[10]	valid_0's l1: 2.32643e+06
[11]	valid_0's l1: 2.23079e+06
[12]	valid_0's l1: 2.18948e+06
[13]	valid_0's l1: 2.10749e+06
[14]	valid_0's l1: 2.08242e+06
[15]	valid_0's l1: 2.01493e+06
[16]	valid_0's l1: 1.95632e+06
[17]	valid_0's l1: 1.90485e+06
[18]	valid_0's l1: 1.86042e+06
[19]	valid_0's l1: 1.82396e+06
[20]	valid_0's l1: 1.79462e+06
[21]	valid_0's l1: 1.76725e+06
[22]	valid_0's l1: 1.7403e+06
[23]	valid_0's l1: 1.71626e+06
[24]	valid_0's l1: 1.69631e+06
[25]	valid_0's l1: 1.67999e+06
[26]	valid_0's l1: 1.66406e+06
[27]	valid_0's l1: 1.65339e+06
[28]	valid_0's l1: 1.64006e+06
[29]	valid_0's l1: 1.63299e+06
[30]	valid_0's l1: 1.63076e+06
[31]	valid_0's l1: 1.6258e+06
[32]	valid_0's l1: 1.62122e+06
[33]	valid_0's l1: 1.616e+06
[34]	valid_0's l1: 1.61383e+06
[35]	valid_0's l1: 1.61383e+06
[36]	valid_0's l1: 1.60584e+06
[37]	valid_0's l1: 1.60486e+06
[38]	valid_0's l1: 1.60448e+06
[39]	valid_0's l1: 1.59697e+06
[40]	valid_0's l1: 1.5953e+06
[41]	valid_0's l1: 1.59587e+06
[42]	valid_0's l1: 1.59189e+06
[43]	valid_0's l1: 1.59228e+06
[44]	valid_0's l1: 1.58958e+06
[45]	valid_0's l1: 1.58835e+06
[46]	valid_0's l1: 1.5905e+06
[47]	valid_0's l1: 1.59163e+06
[48]	valid_0's l1: 1.58945e+06
[49]	valid_0's l1: 1.59093e+06
[50]	valid_0's l1: 1.58741e+06
[51]	valid_0's l1: 1.58842e+06
[52]	valid_0's l1: 1.58895e+06
[53]	valid_0's l1: 1.59036e+06
[54]	valid_0's l1: 1.59301e+06
[55]	valid_0's l1: 1.59183e+06
[56]	valid_0's l1: 1.58957e+06
[57]	valid_0's l1: 1.59206e+06
[58]	valid_0's l1: 1.5917e+06
[59]	valid_0's l1: 1.59371e+06
[60]	valid_0's l1: 1.59457e+06
[61]	valid_0's l1: 1.59512e+06
[62]	valid_0's l1: 1.59525e+06
[63]	valid_0's l1: 1.59274e+06
[64]	valid_0's l1: 1.5912e+06
[65]	valid_0's l1: 1.59183e+06
[66]	valid_0's l1: 1.59296e+06
[67]	valid_0's l1: 1.5923e+06
[68]	valid_0's l1: 1.59439e+06
[69]	valid_0's l1: 1.59513e+06
[70]	valid_0's l1: 1.59526e+06
[71]	valid_0's l1: 1.59688e+06
[72]	valid_0's l1: 1.59705e+06
[73]	valid_0's l1: 1.59793e+06
[74]	valid_0's l1: 1.59769e+06
[75]	valid_0's l1: 1.59656e+06
[76]	valid_0's l1: 1.59516e+06
[77]	valid_0's l1: 1.59735e+06
[78]	valid_0's l1: 1.59631e+06
[79]	valid_0's l1: 1.5967e+06
[80]	valid_0's l1: 1.59598e+06
Early stopping, best iteration is:
[50]	valid_0's l1: 1.58741e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.83364e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.5461e+06
[3]	valid_0's l1: 3.29059e+06
[4]	valid_0's l1: 3.05995e+06
[5]	valid_0's l1: 2.86177e+06
[6]	valid_0's l1: 2.77283e+06
[7]	valid_0's l1: 2.69017e+06
[8]	valid_0's l1: 2.54159e+06
[9]	valid_0's l1: 2.41143e+06
[10]	valid_0's l1: 2.30017e+06
[11]	valid_0's l1: 2.20183e+06
[12]	valid_0's l1: 2.15705e+06
[13]	valid_0's l1: 2.07987e+06
[14]	valid_0's l1: 2.05065e+06
[15]	valid_0's l1: 1.98821e+06
[16]	valid_0's l1: 1.93406e+06
[17]	valid_0's l1: 1.88841e+06
[18]	valid_0's l1: 1.8524e+06
[19]	valid_0's l1: 1.81851e+06
[20]	valid_0's l1: 1.78965e+06
[21]	valid_0's l1: 1.76343e+06
[22]	valid_0's l1: 1.74308e+06
[23]	valid_0's l1: 1.7241e+06
[24]	valid_0's l1: 1.70645e+06
[25]	valid_0's l1: 1.69239e+06
[26]	valid_0's l1: 1.67826e+06
[27]	valid_0's l1: 1.66647e+06
[28]	valid_0's l1: 1.65689e+06
[29]	valid_0's l1: 1.64698e+06
[30]	valid_0's l1: 1.63783e+06
[31]	valid_0's l1: 1.62995e+06
[32]	valid_0's l1: 1.62507e+06
[33]	valid_0's l1: 1.62243e+06
[34]	valid_0's l1: 1.61622e+06
[35]	valid_0's l1: 1.61111e+06
[36]	valid_0's l1: 1.6069e+06
[37]	valid_0's l1: 1.6063e+06
[38]	valid_0's l1: 1.60097e+06
[39]	valid_0's l1: 1.60005e+06
[40]	valid_0's l1: 1.59611e+06
[41]	valid_0's l1: 1.59512e+06
[42]	valid_0's l1: 1.59286e+06
[43]	valid_0's l1: 1.5929e+06
[44]	valid_0's l1: 1.59173e+06
[45]	valid_0's l1: 1.59163e+06
[46]	valid_0's l1: 1.59149e+06
[47]	valid_0's l1: 1.59111e+06
[48]	valid_0's l1: 1.59168e+06
[49]	valid_0's l1: 1.59049e+06
[50]	valid_0's l1: 1.58867e+06
[51]	valid_0's l1: 1.58963e+06
[52]	valid_0's l1: 1.5878e+06
[53]	valid_0's l1: 1.58834e+06
[54]	valid_0's l1: 1.58963e+06
[55]	valid_0's l1: 1.59054e+06
[56]	valid_0's l1: 1.58928e+06
[57]	valid_0's l1: 1.59034e+06
[58]	valid_0's l1: 1.59245e+06
[59]	valid_0's l1: 1.59305e+06
[60]	valid_0's l1: 1.59228e+06
[61]	valid_0's l1: 1.59105e+06
[62]	valid_0's l1: 1.59135e+06
[63]	valid_0's l1: 1.59307e+06
[64]	valid_0's l1: 1.59467e+06
[65]	valid_0's l1: 1.59252e+06
[66]	valid_0's l1: 1.59273e+06
[67]	valid_0's l1: 1.59195e+06
[68]	valid_0's l1: 1.59278e+06
[69]	valid_0's l1: 1.59117e+06
[70]	valid_0's l1: 1.59206e+06
[71]	valid_0's l1: 1.58878e+06
[72]	valid_0's l1: 1.58795e+06
[73]	valid_0's l1: 1.58921e+06
[74]	valid_0's l1: 1.58924e+06
[75]	valid_0's l1: 1.58805e+06
[76]	valid_0's l1: 1.59015e+06
[77]	valid_0's l1: 1.58963e+06
[78]	valid_0's l1: 1.59027e+06
[79]	valid_0's l1: 1.59127e+06
[80]	valid_0's l1: 1.59145e+06
[81]	valid_0's l1: 1.59056e+06
[82]	valid_0's l1: 1.58941e+06
Early stopping, best iteration is:
[52]	valid_0's l1: 1.5878e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.91572e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.61074e+06
[3]	valid_0's l1: 3.33753e+06
[4]	valid_0's l1: 3.10152e+06
[5]	valid_0's l1: 2.89582e+06
[6]	valid_0's l1: 2.79571e+06
[7]	valid_0's l1: 2.70656e+06
[8]	valid_0's l1: 2.55707e+06
[9]	valid_0's l1: 2.42782e+06
[10]	valid_0's l1: 2.31229e+06
[11]	valid_0's l1: 2.20818e+06
[12]	valid_0's l1: 2.16335e+06
[13]	valid_0's l1: 2.08003e+06
[14]	valid_0's l1: 2.05301e+06
[15]	valid_0's l1: 1.99207e+06
[16]	valid_0's l1: 1.94133e+06
[17]	valid_0's l1: 1.89339e+06
[18]	valid_0's l1: 1.85478e+06
[19]	valid_0's l1: 1.8147e+06
[20]	valid_0's l1: 1.78487e+06
[21]	valid_0's l1: 1.75924e+06
[22]	valid_0's l1: 1.74016e+06
[23]	valid_0's l1: 1.71891e+06
[24]	valid_0's l1: 1.70106e+06
[25]	valid_0's l1: 1.68439e+06
[26]	valid_0's l1: 1.67383e+06
[27]	valid_0's l1: 1.65878e+06
[28]	valid_0's l1: 1.649e+06
[29]	valid_0's l1: 1.63901e+06
[30]	valid_0's l1: 1.62905e+06
[31]	valid_0's l1: 1.62759e+06
[32]	valid_0's l1: 1.61952e+06
[33]	valid_0's l1: 1.61689e+06
[34]	valid_0's l1: 1.61312e+06
[35]	valid_0's l1: 1.60736e+06
[36]	valid_0's l1: 1.60514e+06
[37]	valid_0's l1: 1.60376e+06
[38]	valid_0's l1: 1.60592e+06
[39]	valid_0's l1: 1.60543e+06
[40]	valid_0's l1: 1.59799e+06
[41]	valid_0's l1: 1.59851e+06
[42]	valid_0's l1: 1.59751e+06
[43]	valid_0's l1: 1.59811e+06
[44]	valid_0's l1: 1.59782e+06
[45]	valid_0's l1: 1.59742e+06
[46]	valid_0's l1: 1.59288e+06
[47]	valid_0's l1: 1.59251e+06
[48]	valid_0's l1: 1.59195e+06
[49]	valid_0's l1: 1.58928e+06
[50]	valid_0's l1: 1.59053e+06
[51]	valid_0's l1: 1.59081e+06
[52]	valid_0's l1: 1.59059e+06
[53]	valid_0's l1: 1.59177e+06
[54]	valid_0's l1: 1.59203e+06
[55]	valid_0's l1: 1.59381e+06
[56]	valid_0's l1: 1.59399e+06
[57]	valid_0's l1: 1.59315e+06
[58]	valid_0's l1: 1.59266e+06
[59]	valid_0's l1: 1.59384e+06
[60]	valid_0's l1: 1.59174e+06
[61]	valid_0's l1: 1.58921e+06
[62]	valid_0's l1: 1.58785e+06
[63]	valid_0's l1: 1.58523e+06
[64]	valid_0's l1: 1.58298e+06
[65]	valid_0's l1: 1.58113e+06
[66]	valid_0's l1: 1.58106e+06
[67]	valid_0's l1: 1.58116e+06
[68]	valid_0's l1: 1.57942e+06
[69]	valid_0's l1: 1.58066e+06
[70]	valid_0's l1: 1.58022e+06
[71]	valid_0's l1: 1.5808e+06
[72]	valid_0's l1: 1.58208e+06
[73]	valid_0's l1: 1.58456e+06
[74]	valid_0's l1: 1.58385e+06
[75]	valid_0's l1: 1.58498e+06
[76]	valid_0's l1: 1.58434e+06
[77]	valid_0's l1: 1.58475e+06
[78]	valid_0's l1: 1.58145e+06
[79]	valid_0's l1: 1.58196e+06
[80]	valid_0's l1: 1.58417e+06
[81]	valid_0's l1: 1.58494e+06
[82]	valid_0's l1: 1.58513e+06
[83]	valid_0's l1: 1.58645e+06
[84]	valid_0's l1: 1.58739e+06
[85]	valid_0's l1: 1.58657e+06
[86]	valid_0's l1: 1.58803e+06
[87]	valid_0's l1: 1.58818e+06
[88]	valid_0's l1: 1.58914e+06
[89]	valid_0's l1: 1.58878e+06
[90]	valid_0's l1: 1.58933e+06
[91]	valid_0's l1: 1.58835e+06
[92]	valid_0's l1: 1.5869e+06
[93]	valid_0's l1: 1.58721e+06
[94]	valid_0's l1: 1.58837e+06
[95]	valid_0's l1: 1.58912e+06
[96]	valid_0's l1: 1.58927e+06
[97]	valid_0's l1: 1.58881e+06
[98]	valid_0's l1: 1.59116e+06
Early stopping, best iteration is:
[68]	valid_0's l1: 1.57942e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.69405e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1598e+06
[3]	valid_0's l1: 2.76355e+06
[4]	valid_0's l1: 2.45909e+06
[5]	valid_0's l1: 2.24837e+06
[6]	valid_0's l1: 2.17429e+06
[7]	valid_0's l1: 2.11153e+06
[8]	valid_0's l1: 1.98392e+06
[9]	valid_0's l1: 1.89989e+06
[10]	valid_0's l1: 1.8382e+06
[11]	valid_0's l1: 1.78986e+06
[12]	valid_0's l1: 1.77362e+06
[13]	valid_0's l1: 1.74998e+06
[14]	valid_0's l1: 1.7455e+06
[15]	valid_0's l1: 1.72846e+06
[16]	valid_0's l1: 1.71675e+06
[17]	valid_0's l1: 1.71e+06
[18]	valid_0's l1: 1.70856e+06
[19]	valid_0's l1: 1.70935e+06
[20]	valid_0's l1: 1.70615e+06
[21]	valid_0's l1: 1.71159e+06
[22]	valid_0's l1: 1.71179e+06
[23]	valid_0's l1: 1.71527e+06
[24]	valid_0's l1: 1.72176e+06
[25]	valid_0's l1: 1.72737e+06
[26]	valid_0's l1: 1.72886e+06
[27]	valid_0's l1: 1.7298e+06
[28]	valid_0's l1: 1.73337e+06
[29]	valid_0's l1: 1.73864e+06
[30]	valid_0's l1: 1.73277e+06
[31]	valid_0's l1: 1.74082e+06
[32]	valid_0's l1: 1.74536e+06
[33]	valid_0's l1: 1.7446e+06
[34]	valid_0's l1: 1.74336e+06
[35]	valid_0's l1: 1.74879e+06
[36]	valid_0's l1: 1.74662e+06
[37]	valid_0's l1: 1.75018e+06
[38]	valid_0's l1: 1.75158e+06
[39]	valid_0's l1: 1.75496e+06
[40]	valid_0's l1: 1.75484e+06
[41]	valid_0's l1: 1.75695e+06
[42]	valid_0's l1: 1.75627e+06
[43]	valid_0's l1: 1.75882e+06
[44]	valid_0's l1: 1.76028e+06
[45]	valid_0's l1: 1.7591e+06
[46]	valid_0's l1: 1.75985e+06
[47]	valid_0's l1: 1.76132e+06
[48]	valid_0's l1: 1.76081e+06
[49]	valid_0's l1: 1.75987e+06
[50]	valid_0's l1: 1.76197e+06
Early stopping, best iteration is:
[20]	valid_0's l1: 1.70615e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.65312e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.14754e+06
[3]	valid_0's l1: 2.74253e+06
[4]	valid_0's l1: 2.44702e+06
[5]	valid_0's l1: 2.23118e+06
[6]	valid_0's l1: 2.1436e+06
[7]	valid_0's l1: 2.07788e+06
[8]	valid_0's l1: 1.96328e+06
[9]	valid_0's l1: 1.88086e+06
[10]	valid_0's l1: 1.81434e+06
[11]	valid_0's l1: 1.77025e+06
[12]	valid_0's l1: 1.7582e+06
[13]	valid_0's l1: 1.7324e+06
[14]	valid_0's l1: 1.7307e+06
[15]	valid_0's l1: 1.71914e+06
[16]	valid_0's l1: 1.70847e+06
[17]	valid_0's l1: 1.71082e+06
[18]	valid_0's l1: 1.70652e+06
[19]	valid_0's l1: 1.70882e+06
[20]	valid_0's l1: 1.70653e+06
[21]	valid_0's l1: 1.71105e+06
[22]	valid_0's l1: 1.71115e+06
[23]	valid_0's l1: 1.71315e+06
[24]	valid_0's l1: 1.71157e+06
[25]	valid_0's l1: 1.72015e+06
[26]	valid_0's l1: 1.72486e+06
[27]	valid_0's l1: 1.72282e+06
[28]	valid_0's l1: 1.72413e+06
[29]	valid_0's l1: 1.72733e+06
[30]	valid_0's l1: 1.72706e+06
[31]	valid_0's l1: 1.72835e+06
[32]	valid_0's l1: 1.72733e+06
[33]	valid_0's l1: 1.73047e+06
[34]	valid_0's l1: 1.72756e+06
[35]	valid_0's l1: 1.72728e+06
[36]	valid_0's l1: 1.73103e+06
[37]	valid_0's l1: 1.73193e+06
[38]	valid_0's l1: 1.73618e+06
[39]	valid_0's l1: 1.73471e+06
[40]	valid_0's l1: 1.73887e+06
[41]	valid_0's l1: 1.73759e+06
[42]	valid_0's l1: 1.74282e+06
[43]	valid_0's l1: 1.74739e+06
[44]	valid_0's l1: 1.74498e+06
[45]	valid_0's l1: 1.74684e+06
[46]	valid_0's l1: 1.75015e+06
[47]	valid_0's l1: 1.7487e+06
[48]	valid_0's l1: 1.74989e+06
Early stopping, best iteration is:
[18]	valid_0's l1: 1.70652e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.72204e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17054e+06
[3]	valid_0's l1: 2.74648e+06
[4]	valid_0's l1: 2.44099e+06
[5]	valid_0's l1: 2.22643e+06
[6]	valid_0's l1: 2.13949e+06
[7]	valid_0's l1: 2.07147e+06
[8]	valid_0's l1: 1.96228e+06
[9]	valid_0's l1: 1.88236e+06
[10]	valid_0's l1: 1.82206e+06
[11]	valid_0's l1: 1.7695e+06
[12]	valid_0's l1: 1.75469e+06
[13]	valid_0's l1: 1.72994e+06
[14]	valid_0's l1: 1.73225e+06
[15]	valid_0's l1: 1.71957e+06
[16]	valid_0's l1: 1.70141e+06
[17]	valid_0's l1: 1.68815e+06
[18]	valid_0's l1: 1.69655e+06
[19]	valid_0's l1: 1.69964e+06
[20]	valid_0's l1: 1.6935e+06
[21]	valid_0's l1: 1.6906e+06
[22]	valid_0's l1: 1.69327e+06
[23]	valid_0's l1: 1.69228e+06
[24]	valid_0's l1: 1.69521e+06
[25]	valid_0's l1: 1.69694e+06
[26]	valid_0's l1: 1.69293e+06
[27]	valid_0's l1: 1.69643e+06
[28]	valid_0's l1: 1.69572e+06
[29]	valid_0's l1: 1.69559e+06
[30]	valid_0's l1: 1.69489e+06
[31]	valid_0's l1: 1.70033e+06
[32]	valid_0's l1: 1.70343e+06
[33]	valid_0's l1: 1.70433e+06
[34]	valid_0's l1: 1.70409e+06
[35]	valid_0's l1: 1.70692e+06
[36]	valid_0's l1: 1.70936e+06
[37]	valid_0's l1: 1.71489e+06
[38]	valid_0's l1: 1.71212e+06
[39]	valid_0's l1: 1.71647e+06
[40]	valid_0's l1: 1.71969e+06
[41]	valid_0's l1: 1.72057e+06
[42]	valid_0's l1: 1.72345e+06
[43]	valid_0's l1: 1.72367e+06
[44]	valid_0's l1: 1.72635e+06
[45]	valid_0's l1: 1.73191e+06
[46]	valid_0's l1: 1.7332e+06
[47]	valid_0's l1: 1.73282e+06
Early stopping, best iteration is:
[17]	valid_0's l1: 1.68815e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.69457e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.16036e+06
[3]	valid_0's l1: 2.76039e+06
[4]	valid_0's l1: 2.46011e+06
[5]	valid_0's l1: 2.25014e+06
[6]	valid_0's l1: 2.17619e+06
[7]	valid_0's l1: 2.12057e+06
[8]	valid_0's l1: 1.99046e+06
[9]	valid_0's l1: 1.90537e+06
[10]	valid_0's l1: 1.84246e+06
[11]	valid_0's l1: 1.79557e+06
[12]	valid_0's l1: 1.77552e+06
[13]	valid_0's l1: 1.7552e+06
[14]	valid_0's l1: 1.75783e+06
[15]	valid_0's l1: 1.74009e+06
[16]	valid_0's l1: 1.72329e+06
[17]	valid_0's l1: 1.71541e+06
[18]	valid_0's l1: 1.71353e+06
[19]	valid_0's l1: 1.71455e+06
[20]	valid_0's l1: 1.70729e+06
[21]	valid_0's l1: 1.71074e+06
[22]	valid_0's l1: 1.71576e+06
[23]	valid_0's l1: 1.71677e+06
[24]	valid_0's l1: 1.72341e+06
[25]	valid_0's l1: 1.72883e+06
[26]	valid_0's l1: 1.72534e+06
[27]	valid_0's l1: 1.72912e+06
[28]	valid_0's l1: 1.73368e+06
[29]	valid_0's l1: 1.73878e+06
[30]	valid_0's l1: 1.73599e+06
[31]	valid_0's l1: 1.73795e+06
[32]	valid_0's l1: 1.74221e+06
[33]	valid_0's l1: 1.74634e+06
[34]	valid_0's l1: 1.74628e+06
[35]	valid_0's l1: 1.75163e+06
[36]	valid_0's l1: 1.75402e+06
[37]	valid_0's l1: 1.75099e+06
[38]	valid_0's l1: 1.75159e+06
[39]	valid_0's l1: 1.75533e+06
[40]	valid_0's l1: 1.75661e+06
[41]	valid_0's l1: 1.7594e+06
[42]	valid_0's l1: 1.75635e+06
[43]	valid_0's l1: 1.75724e+06
[44]	valid_0's l1: 1.7619e+06
[45]	valid_0's l1: 1.7619e+06
[46]	valid_0's l1: 1.76091e+06
[47]	valid_0's l1: 1.76298e+06
[48]	valid_0's l1: 1.76366e+06
[49]	valid_0's l1: 1.76831e+06
[50]	valid_0's l1: 1.77015e+06
Early stopping, best iteration is:
[20]	valid_0's l1: 1.70729e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.65467e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.14936e+06
[3]	valid_0's l1: 2.7456e+06
[4]	valid_0's l1: 2.44883e+06
[5]	valid_0's l1: 2.23091e+06
[6]	valid_0's l1: 2.13898e+06
[7]	valid_0's l1: 2.07805e+06
[8]	valid_0's l1: 1.97044e+06
[9]	valid_0's l1: 1.89433e+06
[10]	valid_0's l1: 1.8338e+06
[11]	valid_0's l1: 1.79255e+06
[12]	valid_0's l1: 1.78759e+06
[13]	valid_0's l1: 1.75872e+06
[14]	valid_0's l1: 1.75191e+06
[15]	valid_0's l1: 1.74271e+06
[16]	valid_0's l1: 1.73072e+06
[17]	valid_0's l1: 1.72693e+06
[18]	valid_0's l1: 1.72805e+06
[19]	valid_0's l1: 1.72976e+06
[20]	valid_0's l1: 1.72195e+06
[21]	valid_0's l1: 1.72643e+06
[22]	valid_0's l1: 1.72262e+06
[23]	valid_0's l1: 1.7236e+06
[24]	valid_0's l1: 1.72047e+06
[25]	valid_0's l1: 1.72379e+06
[26]	valid_0's l1: 1.72899e+06
[27]	valid_0's l1: 1.72603e+06
[28]	valid_0's l1: 1.72886e+06
[29]	valid_0's l1: 1.72794e+06
[30]	valid_0's l1: 1.72986e+06
[31]	valid_0's l1: 1.73508e+06
[32]	valid_0's l1: 1.73161e+06
[33]	valid_0's l1: 1.73361e+06
[34]	valid_0's l1: 1.72988e+06
[35]	valid_0's l1: 1.73199e+06
[36]	valid_0's l1: 1.73268e+06
[37]	valid_0's l1: 1.73617e+06
[38]	valid_0's l1: 1.73751e+06
[39]	valid_0's l1: 1.73535e+06
[40]	valid_0's l1: 1.73826e+06
[41]	valid_0's l1: 1.74188e+06
[42]	valid_0's l1: 1.74079e+06
[43]	valid_0's l1: 1.74727e+06
[44]	valid_0's l1: 1.74386e+06
[45]	valid_0's l1: 1.7466e+06
[46]	valid_0's l1: 1.74465e+06
[47]	valid_0's l1: 1.74705e+06
[48]	valid_0's l1: 1.74613e+06
[49]	valid_0's l1: 1.74901e+06
[50]	valid_0's l1: 1.74705e+06
[51]	valid_0's l1: 1.74809e+06
[52]	valid_0's l1: 1.7492e+06
[53]	valid_0's l1: 1.75047e+06
[54]	valid_0's l1: 1.7508e+06
Early stopping, best iteration is:
[24]	valid_0's l1: 1.72047e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.72212e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.16752e+06
[3]	valid_0's l1: 2.74658e+06
[4]	valid_0's l1: 2.44054e+06
[5]	valid_0's l1: 2.22549e+06
[6]	valid_0's l1: 2.14158e+06
[7]	valid_0's l1: 2.08181e+06
[8]	valid_0's l1: 1.97017e+06
[9]	valid_0's l1: 1.89011e+06
[10]	valid_0's l1: 1.83723e+06
[11]	valid_0's l1: 1.78618e+06
[12]	valid_0's l1: 1.77151e+06
[13]	valid_0's l1: 1.74297e+06
[14]	valid_0's l1: 1.74896e+06
[15]	valid_0's l1: 1.73828e+06
[16]	valid_0's l1: 1.72576e+06
[17]	valid_0's l1: 1.71663e+06
[18]	valid_0's l1: 1.71738e+06
[19]	valid_0's l1: 1.71398e+06
[20]	valid_0's l1: 1.70916e+06
[21]	valid_0's l1: 1.7073e+06
[22]	valid_0's l1: 1.71162e+06
[23]	valid_0's l1: 1.71532e+06
[24]	valid_0's l1: 1.71218e+06
[25]	valid_0's l1: 1.71308e+06
[26]	valid_0's l1: 1.71093e+06
[27]	valid_0's l1: 1.71039e+06
[28]	valid_0's l1: 1.71325e+06
[29]	valid_0's l1: 1.71475e+06
[30]	valid_0's l1: 1.71906e+06
[31]	valid_0's l1: 1.72529e+06
[32]	valid_0's l1: 1.7273e+06
[33]	valid_0's l1: 1.72672e+06
[34]	valid_0's l1: 1.72911e+06
[35]	valid_0's l1: 1.73121e+06
[36]	valid_0's l1: 1.72691e+06
[37]	valid_0's l1: 1.72494e+06
[38]	valid_0's l1: 1.72654e+06
[39]	valid_0's l1: 1.72893e+06
[40]	valid_0's l1: 1.72876e+06
[41]	valid_0's l1: 1.72963e+06
[42]	valid_0's l1: 1.73378e+06
[43]	valid_0's l1: 1.73461e+06
[44]	valid_0's l1: 1.73571e+06
[45]	valid_0's l1: 1.73816e+06
[46]	valid_0's l1: 1.74112e+06
[47]	valid_0's l1: 1.74109e+06
[48]	valid_0's l1: 1.74229e+06
[49]	valid_0's l1: 1.74099e+06
[50]	valid_0's l1: 1.74137e+06
[51]	valid_0's l1: 1.74264e+06
Early stopping, best iteration is:
[21]	valid_0's l1: 1.7073e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.69405e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1598e+06
[3]	valid_0's l1: 2.76355e+06
[4]	valid_0's l1: 2.45909e+06
[5]	valid_0's l1: 2.24837e+06
[6]	valid_0's l1: 2.17429e+06
[7]	valid_0's l1: 2.11153e+06
[8]	valid_0's l1: 1.98392e+06
[9]	valid_0's l1: 1.89989e+06
[10]	valid_0's l1: 1.8382e+06
[11]	valid_0's l1: 1.78986e+06
[12]	valid_0's l1: 1.77362e+06
[13]	valid_0's l1: 1.74998e+06
[14]	valid_0's l1: 1.7455e+06
[15]	valid_0's l1: 1.72846e+06
[16]	valid_0's l1: 1.71675e+06
[17]	valid_0's l1: 1.71e+06
[18]	valid_0's l1: 1.70856e+06
[19]	valid_0's l1: 1.70935e+06
[20]	valid_0's l1: 1.70615e+06
[21]	valid_0's l1: 1.71159e+06
[22]	valid_0's l1: 1.71179e+06
[23]	valid_0's l1: 1.71527e+06
[24]	valid_0's l1: 1.72176e+06
[25]	valid_0's l1: 1.72737e+06
[26]	valid_0's l1: 1.72886e+06
[27]	valid_0's l1: 1.7298e+06
[28]	valid_0's l1: 1.73337e+06
[29]	valid_0's l1: 1.73864e+06
[30]	valid_0's l1: 1.73277e+06
[31]	valid_0's l1: 1.74082e+06
[32]	valid_0's l1: 1.74536e+06
[33]	valid_0's l1: 1.7446e+06
[34]	valid_0's l1: 1.74336e+06
[35]	valid_0's l1: 1.74879e+06
[36]	valid_0's l1: 1.74662e+06
[37]	valid_0's l1: 1.75018e+06
[38]	valid_0's l1: 1.75158e+06
[39]	valid_0's l1: 1.75496e+06
[40]	valid_0's l1: 1.75484e+06
[41]	valid_0's l1: 1.75695e+06
[42]	valid_0's l1: 1.75627e+06
[43]	valid_0's l1: 1.75882e+06
[44]	valid_0's l1: 1.76028e+06
[45]	valid_0's l1: 1.7591e+06
[46]	valid_0's l1: 1.75985e+06
[47]	valid_0's l1: 1.76132e+06
[48]	valid_0's l1: 1.76081e+06
[49]	valid_0's l1: 1.75987e+06
[50]	valid_0's l1: 1.76197e+06
Early stopping, best iteration is:
[20]	valid_0's l1: 1.70615e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.65312e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.14754e+06
[3]	valid_0's l1: 2.74253e+06
[4]	valid_0's l1: 2.44702e+06
[5]	valid_0's l1: 2.23118e+06
[6]	valid_0's l1: 2.1436e+06
[7]	valid_0's l1: 2.07788e+06
[8]	valid_0's l1: 1.96328e+06
[9]	valid_0's l1: 1.88086e+06
[10]	valid_0's l1: 1.81434e+06
[11]	valid_0's l1: 1.77025e+06
[12]	valid_0's l1: 1.7582e+06
[13]	valid_0's l1: 1.7324e+06
[14]	valid_0's l1: 1.7307e+06
[15]	valid_0's l1: 1.71914e+06
[16]	valid_0's l1: 1.70847e+06
[17]	valid_0's l1: 1.71082e+06
[18]	valid_0's l1: 1.70652e+06
[19]	valid_0's l1: 1.70882e+06
[20]	valid_0's l1: 1.70653e+06
[21]	valid_0's l1: 1.71105e+06
[22]	valid_0's l1: 1.71115e+06
[23]	valid_0's l1: 1.71315e+06
[24]	valid_0's l1: 1.71157e+06
[25]	valid_0's l1: 1.72015e+06
[26]	valid_0's l1: 1.72486e+06
[27]	valid_0's l1: 1.72282e+06
[28]	valid_0's l1: 1.72413e+06
[29]	valid_0's l1: 1.72733e+06
[30]	valid_0's l1: 1.72706e+06
[31]	valid_0's l1: 1.72835e+06
[32]	valid_0's l1: 1.72733e+06
[33]	valid_0's l1: 1.73047e+06
[34]	valid_0's l1: 1.72756e+06
[35]	valid_0's l1: 1.72728e+06
[36]	valid_0's l1: 1.73103e+06
[37]	valid_0's l1: 1.73193e+06
[38]	valid_0's l1: 1.73618e+06
[39]	valid_0's l1: 1.73471e+06
[40]	valid_0's l1: 1.73887e+06
[41]	valid_0's l1: 1.73759e+06
[42]	valid_0's l1: 1.74282e+06
[43]	valid_0's l1: 1.74739e+06
[44]	valid_0's l1: 1.74498e+06
[45]	valid_0's l1: 1.74684e+06
[46]	valid_0's l1: 1.75015e+06
[47]	valid_0's l1: 1.7487e+06
[48]	valid_0's l1: 1.74989e+06
Early stopping, best iteration is:
[18]	valid_0's l1: 1.70652e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.72204e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17054e+06
[3]	valid_0's l1: 2.74648e+06
[4]	valid_0's l1: 2.44099e+06
[5]	valid_0's l1: 2.22643e+06
[6]	valid_0's l1: 2.13949e+06
[7]	valid_0's l1: 2.07147e+06
[8]	valid_0's l1: 1.96228e+06
[9]	valid_0's l1: 1.88236e+06
[10]	valid_0's l1: 1.82206e+06
[11]	valid_0's l1: 1.7695e+06
[12]	valid_0's l1: 1.75469e+06
[13]	valid_0's l1: 1.72994e+06
[14]	valid_0's l1: 1.73225e+06
[15]	valid_0's l1: 1.71957e+06
[16]	valid_0's l1: 1.70141e+06
[17]	valid_0's l1: 1.68815e+06
[18]	valid_0's l1: 1.69655e+06
[19]	valid_0's l1: 1.69964e+06
[20]	valid_0's l1: 1.6935e+06
[21]	valid_0's l1: 1.6906e+06
[22]	valid_0's l1: 1.69327e+06
[23]	valid_0's l1: 1.69228e+06
[24]	valid_0's l1: 1.69521e+06
[25]	valid_0's l1: 1.69694e+06
[26]	valid_0's l1: 1.69293e+06
[27]	valid_0's l1: 1.69643e+06
[28]	valid_0's l1: 1.69572e+06
[29]	valid_0's l1: 1.69559e+06
[30]	valid_0's l1: 1.69489e+06
[31]	valid_0's l1: 1.70033e+06
[32]	valid_0's l1: 1.70343e+06
[33]	valid_0's l1: 1.70433e+06
[34]	valid_0's l1: 1.70409e+06
[35]	valid_0's l1: 1.70692e+06
[36]	valid_0's l1: 1.70936e+06
[37]	valid_0's l1: 1.71489e+06
[38]	valid_0's l1: 1.71212e+06
[39]	valid_0's l1: 1.71647e+06
[40]	valid_0's l1: 1.71969e+06
[41]	valid_0's l1: 1.72057e+06
[42]	valid_0's l1: 1.72345e+06
[43]	valid_0's l1: 1.72367e+06
[44]	valid_0's l1: 1.72635e+06
[45]	valid_0's l1: 1.73191e+06
[46]	valid_0's l1: 1.7332e+06
[47]	valid_0's l1: 1.73282e+06
Early stopping, best iteration is:
[17]	valid_0's l1: 1.68815e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.69457e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.16036e+06
[3]	valid_0's l1: 2.76039e+06
[4]	valid_0's l1: 2.46011e+06
[5]	valid_0's l1: 2.25014e+06
[6]	valid_0's l1: 2.17619e+06
[7]	valid_0's l1: 2.12057e+06
[8]	valid_0's l1: 1.99046e+06
[9]	valid_0's l1: 1.90537e+06
[10]	valid_0's l1: 1.84246e+06
[11]	valid_0's l1: 1.79557e+06
[12]	valid_0's l1: 1.77552e+06
[13]	valid_0's l1: 1.7552e+06
[14]	valid_0's l1: 1.75783e+06
[15]	valid_0's l1: 1.74009e+06
[16]	valid_0's l1: 1.72329e+06
[17]	valid_0's l1: 1.71541e+06
[18]	valid_0's l1: 1.71353e+06
[19]	valid_0's l1: 1.71455e+06
[20]	valid_0's l1: 1.70729e+06
[21]	valid_0's l1: 1.71074e+06
[22]	valid_0's l1: 1.71576e+06
[23]	valid_0's l1: 1.71677e+06
[24]	valid_0's l1: 1.72341e+06
[25]	valid_0's l1: 1.72883e+06
[26]	valid_0's l1: 1.72534e+06
[27]	valid_0's l1: 1.72912e+06
[28]	valid_0's l1: 1.73368e+06
[29]	valid_0's l1: 1.73878e+06
[30]	valid_0's l1: 1.73599e+06
[31]	valid_0's l1: 1.73795e+06
[32]	valid_0's l1: 1.74221e+06
[33]	valid_0's l1: 1.74634e+06
[34]	valid_0's l1: 1.74628e+06
[35]	valid_0's l1: 1.75163e+06
[36]	valid_0's l1: 1.75402e+06
[37]	valid_0's l1: 1.75099e+06
[38]	valid_0's l1: 1.75159e+06
[39]	valid_0's l1: 1.75533e+06
[40]	valid_0's l1: 1.75661e+06
[41]	valid_0's l1: 1.7594e+06
[42]	valid_0's l1: 1.75635e+06
[43]	valid_0's l1: 1.75724e+06
[44]	valid_0's l1: 1.7619e+06
[45]	valid_0's l1: 1.7619e+06
[46]	valid_0's l1: 1.76091e+06
[47]	valid_0's l1: 1.76298e+06
[48]	valid_0's l1: 1.76366e+06
[49]	valid_0's l1: 1.76831e+06
[50]	valid_0's l1: 1.77015e+06
Early stopping, best iteration is:
[20]	valid_0's l1: 1.70729e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.65467e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.14936e+06
[3]	valid_0's l1: 2.7456e+06
[4]	valid_0's l1: 2.44883e+06
[5]	valid_0's l1: 2.23091e+06
[6]	valid_0's l1: 2.13898e+06
[7]	valid_0's l1: 2.07805e+06
[8]	valid_0's l1: 1.97044e+06
[9]	valid_0's l1: 1.89433e+06
[10]	valid_0's l1: 1.8338e+06
[11]	valid_0's l1: 1.79255e+06
[12]	valid_0's l1: 1.78759e+06
[13]	valid_0's l1: 1.75872e+06
[14]	valid_0's l1: 1.75191e+06
[15]	valid_0's l1: 1.74271e+06
[16]	valid_0's l1: 1.73072e+06
[17]	valid_0's l1: 1.72693e+06
[18]	valid_0's l1: 1.72805e+06
[19]	valid_0's l1: 1.72976e+06
[20]	valid_0's l1: 1.72195e+06
[21]	valid_0's l1: 1.72643e+06
[22]	valid_0's l1: 1.72262e+06
[23]	valid_0's l1: 1.7236e+06
[24]	valid_0's l1: 1.72047e+06
[25]	valid_0's l1: 1.72379e+06
[26]	valid_0's l1: 1.72899e+06
[27]	valid_0's l1: 1.72603e+06
[28]	valid_0's l1: 1.72886e+06
[29]	valid_0's l1: 1.72794e+06
[30]	valid_0's l1: 1.72986e+06
[31]	valid_0's l1: 1.73508e+06
[32]	valid_0's l1: 1.73161e+06
[33]	valid_0's l1: 1.73361e+06
[34]	valid_0's l1: 1.72988e+06
[35]	valid_0's l1: 1.73199e+06
[36]	valid_0's l1: 1.73268e+06
[37]	valid_0's l1: 1.73617e+06
[38]	valid_0's l1: 1.73751e+06
[39]	valid_0's l1: 1.73535e+06
[40]	valid_0's l1: 1.73826e+06
[41]	valid_0's l1: 1.74188e+06
[42]	valid_0's l1: 1.74079e+06
[43]	valid_0's l1: 1.74727e+06
[44]	valid_0's l1: 1.74386e+06
[45]	valid_0's l1: 1.7466e+06
[46]	valid_0's l1: 1.74465e+06
[47]	valid_0's l1: 1.74705e+06
[48]	valid_0's l1: 1.74613e+06
[49]	valid_0's l1: 1.74901e+06
[50]	valid_0's l1: 1.74705e+06
[51]	valid_0's l1: 1.74809e+06
[52]	valid_0's l1: 1.7492e+06
[53]	valid_0's l1: 1.75047e+06
[54]	valid_0's l1: 1.7508e+06
Early stopping, best iteration is:
[24]	valid_0's l1: 1.72047e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.72212e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.16752e+06
[3]	valid_0's l1: 2.74658e+06
[4]	valid_0's l1: 2.44054e+06
[5]	valid_0's l1: 2.22549e+06
[6]	valid_0's l1: 2.14158e+06
[7]	valid_0's l1: 2.08181e+06
[8]	valid_0's l1: 1.97017e+06
[9]	valid_0's l1: 1.89011e+06
[10]	valid_0's l1: 1.83723e+06
[11]	valid_0's l1: 1.78618e+06
[12]	valid_0's l1: 1.77151e+06
[13]	valid_0's l1: 1.74297e+06
[14]	valid_0's l1: 1.74896e+06
[15]	valid_0's l1: 1.73828e+06
[16]	valid_0's l1: 1.72576e+06
[17]	valid_0's l1: 1.71663e+06
[18]	valid_0's l1: 1.71738e+06
[19]	valid_0's l1: 1.71398e+06
[20]	valid_0's l1: 1.70916e+06
[21]	valid_0's l1: 1.7073e+06
[22]	valid_0's l1: 1.71162e+06
[23]	valid_0's l1: 1.71532e+06
[24]	valid_0's l1: 1.71218e+06
[25]	valid_0's l1: 1.71308e+06
[26]	valid_0's l1: 1.71093e+06
[27]	valid_0's l1: 1.71039e+06
[28]	valid_0's l1: 1.71325e+06
[29]	valid_0's l1: 1.71475e+06
[30]	valid_0's l1: 1.71906e+06
[31]	valid_0's l1: 1.72529e+06
[32]	valid_0's l1: 1.7273e+06
[33]	valid_0's l1: 1.72672e+06
[34]	valid_0's l1: 1.72911e+06
[35]	valid_0's l1: 1.73121e+06
[36]	valid_0's l1: 1.72691e+06
[37]	valid_0's l1: 1.72494e+06
[38]	valid_0's l1: 1.72654e+06
[39]	valid_0's l1: 1.72893e+06
[40]	valid_0's l1: 1.72876e+06
[41]	valid_0's l1: 1.72963e+06
[42]	valid_0's l1: 1.73378e+06
[43]	valid_0's l1: 1.73461e+06
[44]	valid_0's l1: 1.73571e+06
[45]	valid_0's l1: 1.73816e+06
[46]	valid_0's l1: 1.74112e+06
[47]	valid_0's l1: 1.74109e+06
[48]	valid_0's l1: 1.74229e+06
[49]	valid_0's l1: 1.74099e+06
[50]	valid_0's l1: 1.74137e+06
[51]	valid_0's l1: 1.74264e+06
Early stopping, best iteration is:
[21]	valid_0's l1: 1.7073e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.69405e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1598e+06
[3]	valid_0's l1: 2.76355e+06
[4]	valid_0's l1: 2.45909e+06
[5]	valid_0's l1: 2.24837e+06
[6]	valid_0's l1: 2.17429e+06
[7]	valid_0's l1: 2.11153e+06
[8]	valid_0's l1: 1.98392e+06
[9]	valid_0's l1: 1.89989e+06
[10]	valid_0's l1: 1.8382e+06
[11]	valid_0's l1: 1.78986e+06
[12]	valid_0's l1: 1.77362e+06
[13]	valid_0's l1: 1.74998e+06
[14]	valid_0's l1: 1.7455e+06
[15]	valid_0's l1: 1.72846e+06
[16]	valid_0's l1: 1.71675e+06
[17]	valid_0's l1: 1.71e+06
[18]	valid_0's l1: 1.70856e+06
[19]	valid_0's l1: 1.70935e+06
[20]	valid_0's l1: 1.70615e+06
[21]	valid_0's l1: 1.71159e+06
[22]	valid_0's l1: 1.71179e+06
[23]	valid_0's l1: 1.71527e+06
[24]	valid_0's l1: 1.72176e+06
[25]	valid_0's l1: 1.72737e+06
[26]	valid_0's l1: 1.72886e+06
[27]	valid_0's l1: 1.7298e+06
[28]	valid_0's l1: 1.73337e+06
[29]	valid_0's l1: 1.73864e+06
[30]	valid_0's l1: 1.73277e+06
[31]	valid_0's l1: 1.74082e+06
[32]	valid_0's l1: 1.74536e+06
[33]	valid_0's l1: 1.7446e+06
[34]	valid_0's l1: 1.74336e+06
[35]	valid_0's l1: 1.74879e+06
[36]	valid_0's l1: 1.74662e+06
[37]	valid_0's l1: 1.75018e+06
[38]	valid_0's l1: 1.75158e+06
[39]	valid_0's l1: 1.75496e+06
[40]	valid_0's l1: 1.75484e+06
[41]	valid_0's l1: 1.75695e+06
[42]	valid_0's l1: 1.75627e+06
[43]	valid_0's l1: 1.75882e+06
[44]	valid_0's l1: 1.76028e+06
[45]	valid_0's l1: 1.7591e+06
[46]	valid_0's l1: 1.75985e+06
[47]	valid_0's l1: 1.76132e+06
[48]	valid_0's l1: 1.76081e+06
[49]	valid_0's l1: 1.75987e+06
[50]	valid_0's l1: 1.76197e+06
Early stopping, best iteration is:
[20]	valid_0's l1: 1.70615e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.65312e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.14754e+06
[3]	valid_0's l1: 2.74253e+06
[4]	valid_0's l1: 2.44702e+06
[5]	valid_0's l1: 2.23118e+06
[6]	valid_0's l1: 2.1436e+06
[7]	valid_0's l1: 2.07788e+06
[8]	valid_0's l1: 1.96328e+06
[9]	valid_0's l1: 1.88086e+06
[10]	valid_0's l1: 1.81434e+06
[11]	valid_0's l1: 1.77025e+06
[12]	valid_0's l1: 1.7582e+06
[13]	valid_0's l1: 1.7324e+06
[14]	valid_0's l1: 1.7307e+06
[15]	valid_0's l1: 1.71914e+06
[16]	valid_0's l1: 1.70847e+06
[17]	valid_0's l1: 1.71082e+06
[18]	valid_0's l1: 1.70652e+06
[19]	valid_0's l1: 1.70882e+06
[20]	valid_0's l1: 1.70653e+06
[21]	valid_0's l1: 1.71105e+06
[22]	valid_0's l1: 1.71115e+06
[23]	valid_0's l1: 1.71315e+06
[24]	valid_0's l1: 1.71157e+06
[25]	valid_0's l1: 1.72015e+06
[26]	valid_0's l1: 1.72486e+06
[27]	valid_0's l1: 1.72282e+06
[28]	valid_0's l1: 1.72413e+06
[29]	valid_0's l1: 1.72733e+06
[30]	valid_0's l1: 1.72706e+06
[31]	valid_0's l1: 1.72835e+06
[32]	valid_0's l1: 1.72733e+06
[33]	valid_0's l1: 1.73047e+06
[34]	valid_0's l1: 1.72756e+06
[35]	valid_0's l1: 1.72728e+06
[36]	valid_0's l1: 1.73103e+06
[37]	valid_0's l1: 1.73193e+06
[38]	valid_0's l1: 1.73618e+06
[39]	valid_0's l1: 1.73471e+06
[40]	valid_0's l1: 1.73887e+06
[41]	valid_0's l1: 1.73759e+06
[42]	valid_0's l1: 1.74282e+06
[43]	valid_0's l1: 1.74739e+06
[44]	valid_0's l1: 1.74498e+06
[45]	valid_0's l1: 1.74684e+06
[46]	valid_0's l1: 1.75015e+06
[47]	valid_0's l1: 1.7487e+06
[48]	valid_0's l1: 1.74989e+06
Early stopping, best iteration is:
[18]	valid_0's l1: 1.70652e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.72204e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17054e+06
[3]	valid_0's l1: 2.74648e+06
[4]	valid_0's l1: 2.44099e+06
[5]	valid_0's l1: 2.22643e+06
[6]	valid_0's l1: 2.13949e+06
[7]	valid_0's l1: 2.07147e+06
[8]	valid_0's l1: 1.96228e+06
[9]	valid_0's l1: 1.88236e+06
[10]	valid_0's l1: 1.82206e+06
[11]	valid_0's l1: 1.7695e+06
[12]	valid_0's l1: 1.75469e+06
[13]	valid_0's l1: 1.72994e+06
[14]	valid_0's l1: 1.73225e+06
[15]	valid_0's l1: 1.71957e+06
[16]	valid_0's l1: 1.70141e+06
[17]	valid_0's l1: 1.68815e+06
[18]	valid_0's l1: 1.69655e+06
[19]	valid_0's l1: 1.69964e+06
[20]	valid_0's l1: 1.6935e+06
[21]	valid_0's l1: 1.6906e+06
[22]	valid_0's l1: 1.69327e+06
[23]	valid_0's l1: 1.69228e+06
[24]	valid_0's l1: 1.69521e+06
[25]	valid_0's l1: 1.69694e+06
[26]	valid_0's l1: 1.69293e+06
[27]	valid_0's l1: 1.69643e+06
[28]	valid_0's l1: 1.69572e+06
[29]	valid_0's l1: 1.69559e+06
[30]	valid_0's l1: 1.69489e+06
[31]	valid_0's l1: 1.70033e+06
[32]	valid_0's l1: 1.70343e+06
[33]	valid_0's l1: 1.70433e+06
[34]	valid_0's l1: 1.70409e+06
[35]	valid_0's l1: 1.70692e+06
[36]	valid_0's l1: 1.70936e+06
[37]	valid_0's l1: 1.71489e+06
[38]	valid_0's l1: 1.71212e+06
[39]	valid_0's l1: 1.71647e+06
[40]	valid_0's l1: 1.71969e+06
[41]	valid_0's l1: 1.72057e+06
[42]	valid_0's l1: 1.72345e+06
[43]	valid_0's l1: 1.72367e+06
[44]	valid_0's l1: 1.72635e+06
[45]	valid_0's l1: 1.73191e+06
[46]	valid_0's l1: 1.7332e+06
[47]	valid_0's l1: 1.73282e+06
Early stopping, best iteration is:
[17]	valid_0's l1: 1.68815e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.69457e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.16036e+06
[3]	valid_0's l1: 2.76039e+06
[4]	valid_0's l1: 2.46011e+06
[5]	valid_0's l1: 2.25014e+06
[6]	valid_0's l1: 2.17619e+06
[7]	valid_0's l1: 2.12057e+06
[8]	valid_0's l1: 1.99046e+06
[9]	valid_0's l1: 1.90537e+06
[10]	valid_0's l1: 1.84246e+06
[11]	valid_0's l1: 1.79557e+06
[12]	valid_0's l1: 1.77552e+06
[13]	valid_0's l1: 1.7552e+06
[14]	valid_0's l1: 1.75783e+06
[15]	valid_0's l1: 1.74009e+06
[16]	valid_0's l1: 1.72329e+06
[17]	valid_0's l1: 1.71541e+06
[18]	valid_0's l1: 1.71353e+06
[19]	valid_0's l1: 1.71455e+06
[20]	valid_0's l1: 1.70729e+06
[21]	valid_0's l1: 1.71074e+06
[22]	valid_0's l1: 1.71576e+06
[23]	valid_0's l1: 1.71677e+06
[24]	valid_0's l1: 1.72341e+06
[25]	valid_0's l1: 1.72883e+06
[26]	valid_0's l1: 1.72534e+06
[27]	valid_0's l1: 1.72912e+06
[28]	valid_0's l1: 1.73368e+06
[29]	valid_0's l1: 1.73878e+06
[30]	valid_0's l1: 1.73599e+06
[31]	valid_0's l1: 1.73795e+06
[32]	valid_0's l1: 1.74221e+06
[33]	valid_0's l1: 1.74634e+06
[34]	valid_0's l1: 1.74628e+06
[35]	valid_0's l1: 1.75163e+06
[36]	valid_0's l1: 1.75402e+06
[37]	valid_0's l1: 1.75099e+06
[38]	valid_0's l1: 1.75159e+06
[39]	valid_0's l1: 1.75533e+06
[40]	valid_0's l1: 1.75661e+06
[41]	valid_0's l1: 1.7594e+06
[42]	valid_0's l1: 1.75635e+06
[43]	valid_0's l1: 1.75724e+06
[44]	valid_0's l1: 1.7619e+06
[45]	valid_0's l1: 1.7619e+06
[46]	valid_0's l1: 1.76091e+06
[47]	valid_0's l1: 1.76298e+06
[48]	valid_0's l1: 1.76366e+06
[49]	valid_0's l1: 1.76831e+06
[50]	valid_0's l1: 1.77015e+06
Early stopping, best iteration is:
[20]	valid_0's l1: 1.70729e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.65467e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.14936e+06
[3]	valid_0's l1: 2.7456e+06
[4]	valid_0's l1: 2.44883e+06
[5]	valid_0's l1: 2.23091e+06
[6]	valid_0's l1: 2.13898e+06
[7]	valid_0's l1: 2.07805e+06
[8]	valid_0's l1: 1.97044e+06
[9]	valid_0's l1: 1.89433e+06
[10]	valid_0's l1: 1.8338e+06
[11]	valid_0's l1: 1.79255e+06
[12]	valid_0's l1: 1.78759e+06
[13]	valid_0's l1: 1.75872e+06
[14]	valid_0's l1: 1.75191e+06
[15]	valid_0's l1: 1.74271e+06
[16]	valid_0's l1: 1.73072e+06
[17]	valid_0's l1: 1.72693e+06
[18]	valid_0's l1: 1.72805e+06
[19]	valid_0's l1: 1.72976e+06
[20]	valid_0's l1: 1.72195e+06
[21]	valid_0's l1: 1.72643e+06
[22]	valid_0's l1: 1.72262e+06
[23]	valid_0's l1: 1.7236e+06
[24]	valid_0's l1: 1.72047e+06
[25]	valid_0's l1: 1.72379e+06
[26]	valid_0's l1: 1.72899e+06
[27]	valid_0's l1: 1.72603e+06
[28]	valid_0's l1: 1.72886e+06
[29]	valid_0's l1: 1.72794e+06
[30]	valid_0's l1: 1.72986e+06
[31]	valid_0's l1: 1.73508e+06
[32]	valid_0's l1: 1.73161e+06
[33]	valid_0's l1: 1.73361e+06
[34]	valid_0's l1: 1.72988e+06
[35]	valid_0's l1: 1.73199e+06
[36]	valid_0's l1: 1.73268e+06
[37]	valid_0's l1: 1.73617e+06
[38]	valid_0's l1: 1.73751e+06
[39]	valid_0's l1: 1.73535e+06
[40]	valid_0's l1: 1.73826e+06
[41]	valid_0's l1: 1.74188e+06
[42]	valid_0's l1: 1.74079e+06
[43]	valid_0's l1: 1.74727e+06
[44]	valid_0's l1: 1.74386e+06
[45]	valid_0's l1: 1.7466e+06
[46]	valid_0's l1: 1.74465e+06
[47]	valid_0's l1: 1.74705e+06
[48]	valid_0's l1: 1.74613e+06
[49]	valid_0's l1: 1.74901e+06
[50]	valid_0's l1: 1.74705e+06
[51]	valid_0's l1: 1.74809e+06
[52]	valid_0's l1: 1.7492e+06
[53]	valid_0's l1: 1.75047e+06
[54]	valid_0's l1: 1.7508e+06
Early stopping, best iteration is:
[24]	valid_0's l1: 1.72047e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.72212e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.16752e+06
[3]	valid_0's l1: 2.74658e+06
[4]	valid_0's l1: 2.44054e+06
[5]	valid_0's l1: 2.22549e+06
[6]	valid_0's l1: 2.14158e+06
[7]	valid_0's l1: 2.08181e+06
[8]	valid_0's l1: 1.97017e+06
[9]	valid_0's l1: 1.89011e+06
[10]	valid_0's l1: 1.83723e+06
[11]	valid_0's l1: 1.78618e+06
[12]	valid_0's l1: 1.77151e+06
[13]	valid_0's l1: 1.74297e+06
[14]	valid_0's l1: 1.74896e+06
[15]	valid_0's l1: 1.73828e+06
[16]	valid_0's l1: 1.72576e+06
[17]	valid_0's l1: 1.71663e+06
[18]	valid_0's l1: 1.71738e+06
[19]	valid_0's l1: 1.71398e+06
[20]	valid_0's l1: 1.70916e+06
[21]	valid_0's l1: 1.7073e+06
[22]	valid_0's l1: 1.71162e+06
[23]	valid_0's l1: 1.71532e+06
[24]	valid_0's l1: 1.71218e+06
[25]	valid_0's l1: 1.71308e+06
[26]	valid_0's l1: 1.71093e+06
[27]	valid_0's l1: 1.71039e+06
[28]	valid_0's l1: 1.71325e+06
[29]	valid_0's l1: 1.71475e+06
[30]	valid_0's l1: 1.71906e+06
[31]	valid_0's l1: 1.72529e+06
[32]	valid_0's l1: 1.7273e+06
[33]	valid_0's l1: 1.72672e+06
[34]	valid_0's l1: 1.72911e+06
[35]	valid_0's l1: 1.73121e+06
[36]	valid_0's l1: 1.72691e+06
[37]	valid_0's l1: 1.72494e+06
[38]	valid_0's l1: 1.72654e+06
[39]	valid_0's l1: 1.72893e+06
[40]	valid_0's l1: 1.72876e+06
[41]	valid_0's l1: 1.72963e+06
[42]	valid_0's l1: 1.73378e+06
[43]	valid_0's l1: 1.73461e+06
[44]	valid_0's l1: 1.73571e+06
[45]	valid_0's l1: 1.73816e+06
[46]	valid_0's l1: 1.74112e+06
[47]	valid_0's l1: 1.74109e+06
[48]	valid_0's l1: 1.74229e+06
[49]	valid_0's l1: 1.74099e+06
[50]	valid_0's l1: 1.74137e+06
[51]	valid_0's l1: 1.74264e+06
Early stopping, best iteration is:
[21]	valid_0's l1: 1.7073e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7301e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1745e+06
[3]	valid_0's l1: 2.77688e+06
[4]	valid_0's l1: 2.47445e+06
[5]	valid_0's l1: 2.26323e+06
[6]	valid_0's l1: 2.20126e+06
[7]	valid_0's l1: 2.15119e+06
[8]	valid_0's l1: 2.01153e+06
[9]	valid_0's l1: 1.90874e+06
[10]	valid_0's l1: 1.84571e+06
[11]	valid_0's l1: 1.78861e+06
[12]	valid_0's l1: 1.77501e+06
[13]	valid_0's l1: 1.7415e+06
[14]	valid_0's l1: 1.73695e+06
[15]	valid_0's l1: 1.71664e+06
[16]	valid_0's l1: 1.70057e+06
[17]	valid_0's l1: 1.68575e+06
[18]	valid_0's l1: 1.68101e+06
[19]	valid_0's l1: 1.66905e+06
[20]	valid_0's l1: 1.66859e+06
[21]	valid_0's l1: 1.67162e+06
[22]	valid_0's l1: 1.6639e+06
[23]	valid_0's l1: 1.66392e+06
[24]	valid_0's l1: 1.65765e+06
[25]	valid_0's l1: 1.65855e+06
[26]	valid_0's l1: 1.66059e+06
[27]	valid_0's l1: 1.65435e+06
[28]	valid_0's l1: 1.65028e+06
[29]	valid_0's l1: 1.64869e+06
[30]	valid_0's l1: 1.64393e+06
[31]	valid_0's l1: 1.64521e+06
[32]	valid_0's l1: 1.6455e+06
[33]	valid_0's l1: 1.64542e+06
[34]	valid_0's l1: 1.64099e+06
[35]	valid_0's l1: 1.64512e+06
[36]	valid_0's l1: 1.64712e+06
[37]	valid_0's l1: 1.64712e+06
[38]	valid_0's l1: 1.64563e+06
[39]	valid_0's l1: 1.64968e+06
[40]	valid_0's l1: 1.65098e+06
[41]	valid_0's l1: 1.64928e+06
[42]	valid_0's l1: 1.64421e+06
[43]	valid_0's l1: 1.64426e+06
[44]	valid_0's l1: 1.64907e+06
[45]	valid_0's l1: 1.6469e+06
[46]	valid_0's l1: 1.64921e+06
[47]	valid_0's l1: 1.65081e+06
[48]	valid_0's l1: 1.65122e+06
[49]	valid_0's l1: 1.65125e+06
[50]	valid_0's l1: 1.65428e+06
[51]	valid_0's l1: 1.65118e+06
[52]	valid_0's l1: 1.6508e+06
[53]	valid_0's l1: 1.65457e+06
[54]	valid_0's l1: 1.65743e+06
[55]	valid_0's l1: 1.65928e+06
[56]	valid_0's l1: 1.65673e+06
[57]	valid_0's l1: 1.65866e+06
[58]	valid_0's l1: 1.66043e+06
[59]	valid_0's l1: 1.65911e+06
[60]	valid_0's l1: 1.65978e+06
[61]	valid_0's l1: 1.66008e+06
[62]	valid_0's l1: 1.65961e+06
[63]	valid_0's l1: 1.65945e+06
[64]	valid_0's l1: 1.66602e+06
Early stopping, best iteration is:
[34]	valid_0's l1: 1.64099e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.68661e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1591e+06
[3]	valid_0's l1: 2.75499e+06
[4]	valid_0's l1: 2.45416e+06
[5]	valid_0's l1: 2.23723e+06
[6]	valid_0's l1: 2.1592e+06
[7]	valid_0's l1: 2.10718e+06
[8]	valid_0's l1: 1.98413e+06
[9]	valid_0's l1: 1.89977e+06
[10]	valid_0's l1: 1.83449e+06
[11]	valid_0's l1: 1.78458e+06
[12]	valid_0's l1: 1.76969e+06
[13]	valid_0's l1: 1.73441e+06
[14]	valid_0's l1: 1.73006e+06
[15]	valid_0's l1: 1.7097e+06
[16]	valid_0's l1: 1.69813e+06
[17]	valid_0's l1: 1.69385e+06
[18]	valid_0's l1: 1.67542e+06
[19]	valid_0's l1: 1.66869e+06
[20]	valid_0's l1: 1.66645e+06
[21]	valid_0's l1: 1.66198e+06
[22]	valid_0's l1: 1.663e+06
[23]	valid_0's l1: 1.65616e+06
[24]	valid_0's l1: 1.65922e+06
[25]	valid_0's l1: 1.65335e+06
[26]	valid_0's l1: 1.6563e+06
[27]	valid_0's l1: 1.65191e+06
[28]	valid_0's l1: 1.65176e+06
[29]	valid_0's l1: 1.6513e+06
[30]	valid_0's l1: 1.64843e+06
[31]	valid_0's l1: 1.65164e+06
[32]	valid_0's l1: 1.64712e+06
[33]	valid_0's l1: 1.64766e+06
[34]	valid_0's l1: 1.6514e+06
[35]	valid_0's l1: 1.65158e+06
[36]	valid_0's l1: 1.65444e+06
[37]	valid_0's l1: 1.6581e+06
[38]	valid_0's l1: 1.65599e+06
[39]	valid_0's l1: 1.65938e+06
[40]	valid_0's l1: 1.66228e+06
[41]	valid_0's l1: 1.66307e+06
[42]	valid_0's l1: 1.66281e+06
[43]	valid_0's l1: 1.66354e+06
[44]	valid_0's l1: 1.6595e+06
[45]	valid_0's l1: 1.66067e+06
[46]	valid_0's l1: 1.65911e+06
[47]	valid_0's l1: 1.66115e+06
[48]	valid_0's l1: 1.65837e+06
[49]	valid_0's l1: 1.65968e+06
[50]	valid_0's l1: 1.65673e+06
[51]	valid_0's l1: 1.65973e+06
[52]	valid_0's l1: 1.6606e+06
[53]	valid_0's l1: 1.6596e+06
[54]	valid_0's l1: 1.66112e+06
[55]	valid_0's l1: 1.65963e+06
[56]	valid_0's l1: 1.66089e+06
[57]	valid_0's l1: 1.65919e+06
[58]	valid_0's l1: 1.6567e+06
[59]	valid_0's l1: 1.65635e+06
[60]	valid_0's l1: 1.65687e+06
[61]	valid_0's l1: 1.65557e+06
[62]	valid_0's l1: 1.65768e+06
Early stopping, best iteration is:
[32]	valid_0's l1: 1.64712e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.75296e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.19259e+06
[3]	valid_0's l1: 2.7636e+06
[4]	valid_0's l1: 2.45106e+06
[5]	valid_0's l1: 2.23614e+06
[6]	valid_0's l1: 2.17392e+06
[7]	valid_0's l1: 2.12559e+06
[8]	valid_0's l1: 1.99899e+06
[9]	valid_0's l1: 1.9085e+06
[10]	valid_0's l1: 1.83877e+06
[11]	valid_0's l1: 1.78734e+06
[12]	valid_0's l1: 1.75899e+06
[13]	valid_0's l1: 1.71648e+06
[14]	valid_0's l1: 1.71539e+06
[15]	valid_0's l1: 1.68911e+06
[16]	valid_0's l1: 1.67195e+06
[17]	valid_0's l1: 1.65462e+06
[18]	valid_0's l1: 1.65416e+06
[19]	valid_0's l1: 1.65014e+06
[20]	valid_0's l1: 1.64412e+06
[21]	valid_0's l1: 1.6371e+06
[22]	valid_0's l1: 1.63928e+06
[23]	valid_0's l1: 1.63282e+06
[24]	valid_0's l1: 1.63717e+06
[25]	valid_0's l1: 1.63757e+06
[26]	valid_0's l1: 1.63509e+06
[27]	valid_0's l1: 1.63896e+06
[28]	valid_0's l1: 1.63966e+06
[29]	valid_0's l1: 1.6405e+06
[30]	valid_0's l1: 1.64241e+06
[31]	valid_0's l1: 1.64361e+06
[32]	valid_0's l1: 1.64613e+06
[33]	valid_0's l1: 1.64798e+06
[34]	valid_0's l1: 1.64872e+06
[35]	valid_0's l1: 1.64828e+06
[36]	valid_0's l1: 1.64506e+06
[37]	valid_0's l1: 1.64929e+06
[38]	valid_0's l1: 1.64905e+06
[39]	valid_0's l1: 1.65143e+06
[40]	valid_0's l1: 1.64509e+06
[41]	valid_0's l1: 1.64443e+06
[42]	valid_0's l1: 1.64504e+06
[43]	valid_0's l1: 1.64629e+06
[44]	valid_0's l1: 1.64587e+06
[45]	valid_0's l1: 1.64659e+06
[46]	valid_0's l1: 1.6472e+06
[47]	valid_0's l1: 1.65008e+06
[48]	valid_0's l1: 1.65641e+06
[49]	valid_0's l1: 1.65651e+06
[50]	valid_0's l1: 1.65755e+06
[51]	valid_0's l1: 1.65789e+06
[52]	valid_0's l1: 1.65927e+06
[53]	valid_0's l1: 1.65914e+06
Early stopping, best iteration is:
[23]	valid_0's l1: 1.63282e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7301e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1745e+06
[3]	valid_0's l1: 2.77688e+06
[4]	valid_0's l1: 2.47445e+06
[5]	valid_0's l1: 2.26323e+06
[6]	valid_0's l1: 2.20126e+06
[7]	valid_0's l1: 2.15119e+06
[8]	valid_0's l1: 2.01153e+06
[9]	valid_0's l1: 1.90874e+06
[10]	valid_0's l1: 1.84571e+06
[11]	valid_0's l1: 1.78861e+06
[12]	valid_0's l1: 1.77501e+06
[13]	valid_0's l1: 1.7415e+06
[14]	valid_0's l1: 1.73695e+06
[15]	valid_0's l1: 1.71664e+06
[16]	valid_0's l1: 1.70057e+06
[17]	valid_0's l1: 1.68575e+06
[18]	valid_0's l1: 1.68101e+06
[19]	valid_0's l1: 1.66905e+06
[20]	valid_0's l1: 1.66859e+06
[21]	valid_0's l1: 1.67162e+06
[22]	valid_0's l1: 1.6639e+06
[23]	valid_0's l1: 1.66392e+06
[24]	valid_0's l1: 1.65765e+06
[25]	valid_0's l1: 1.65855e+06
[26]	valid_0's l1: 1.66059e+06
[27]	valid_0's l1: 1.65435e+06
[28]	valid_0's l1: 1.65028e+06
[29]	valid_0's l1: 1.64869e+06
[30]	valid_0's l1: 1.64393e+06
[31]	valid_0's l1: 1.64521e+06
[32]	valid_0's l1: 1.6455e+06
[33]	valid_0's l1: 1.64542e+06
[34]	valid_0's l1: 1.64099e+06
[35]	valid_0's l1: 1.64512e+06
[36]	valid_0's l1: 1.64712e+06
[37]	valid_0's l1: 1.64712e+06
[38]	valid_0's l1: 1.64563e+06
[39]	valid_0's l1: 1.64968e+06
[40]	valid_0's l1: 1.65098e+06
[41]	valid_0's l1: 1.64928e+06
[42]	valid_0's l1: 1.64421e+06
[43]	valid_0's l1: 1.64426e+06
[44]	valid_0's l1: 1.64907e+06
[45]	valid_0's l1: 1.6469e+06
[46]	valid_0's l1: 1.64921e+06
[47]	valid_0's l1: 1.65081e+06
[48]	valid_0's l1: 1.65122e+06
[49]	valid_0's l1: 1.65125e+06
[50]	valid_0's l1: 1.65428e+06
[51]	valid_0's l1: 1.65118e+06
[52]	valid_0's l1: 1.6508e+06
[53]	valid_0's l1: 1.65457e+06
[54]	valid_0's l1: 1.65743e+06
[55]	valid_0's l1: 1.65928e+06
[56]	valid_0's l1: 1.65673e+06
[57]	valid_0's l1: 1.65866e+06
[58]	valid_0's l1: 1.66043e+06
[59]	valid_0's l1: 1.65911e+06
[60]	valid_0's l1: 1.65978e+06
[61]	valid_0's l1: 1.66008e+06
[62]	valid_0's l1: 1.65961e+06
[63]	valid_0's l1: 1.65945e+06
[64]	valid_0's l1: 1.66602e+06
Early stopping, best iteration is:
[34]	valid_0's l1: 1.64099e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.68661e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1591e+06
[3]	valid_0's l1: 2.75499e+06
[4]	valid_0's l1: 2.45416e+06
[5]	valid_0's l1: 2.23723e+06
[6]	valid_0's l1: 2.1592e+06
[7]	valid_0's l1: 2.10718e+06
[8]	valid_0's l1: 1.98413e+06
[9]	valid_0's l1: 1.89977e+06
[10]	valid_0's l1: 1.83449e+06
[11]	valid_0's l1: 1.78458e+06
[12]	valid_0's l1: 1.76969e+06
[13]	valid_0's l1: 1.73441e+06
[14]	valid_0's l1: 1.73006e+06
[15]	valid_0's l1: 1.7097e+06
[16]	valid_0's l1: 1.69813e+06
[17]	valid_0's l1: 1.69385e+06
[18]	valid_0's l1: 1.67542e+06
[19]	valid_0's l1: 1.66869e+06
[20]	valid_0's l1: 1.66645e+06
[21]	valid_0's l1: 1.66198e+06
[22]	valid_0's l1: 1.663e+06
[23]	valid_0's l1: 1.65616e+06
[24]	valid_0's l1: 1.65922e+06
[25]	valid_0's l1: 1.65335e+06
[26]	valid_0's l1: 1.6563e+06
[27]	valid_0's l1: 1.65191e+06
[28]	valid_0's l1: 1.65176e+06
[29]	valid_0's l1: 1.6513e+06
[30]	valid_0's l1: 1.64843e+06
[31]	valid_0's l1: 1.65164e+06
[32]	valid_0's l1: 1.64712e+06
[33]	valid_0's l1: 1.64766e+06
[34]	valid_0's l1: 1.6514e+06
[35]	valid_0's l1: 1.65158e+06
[36]	valid_0's l1: 1.65444e+06
[37]	valid_0's l1: 1.6581e+06
[38]	valid_0's l1: 1.65599e+06
[39]	valid_0's l1: 1.65938e+06
[40]	valid_0's l1: 1.66228e+06
[41]	valid_0's l1: 1.66307e+06
[42]	valid_0's l1: 1.66281e+06
[43]	valid_0's l1: 1.66354e+06
[44]	valid_0's l1: 1.6595e+06
[45]	valid_0's l1: 1.66067e+06
[46]	valid_0's l1: 1.65911e+06
[47]	valid_0's l1: 1.66115e+06
[48]	valid_0's l1: 1.65837e+06
[49]	valid_0's l1: 1.65968e+06
[50]	valid_0's l1: 1.65673e+06
[51]	valid_0's l1: 1.65973e+06
[52]	valid_0's l1: 1.6606e+06
[53]	valid_0's l1: 1.6596e+06
[54]	valid_0's l1: 1.66112e+06
[55]	valid_0's l1: 1.65963e+06
[56]	valid_0's l1: 1.66089e+06
[57]	valid_0's l1: 1.65919e+06
[58]	valid_0's l1: 1.6567e+06
[59]	valid_0's l1: 1.65635e+06
[60]	valid_0's l1: 1.65687e+06
[61]	valid_0's l1: 1.65557e+06
[62]	valid_0's l1: 1.65768e+06
Early stopping, best iteration is:
[32]	valid_0's l1: 1.64712e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.75296e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.19259e+06
[3]	valid_0's l1: 2.7636e+06
[4]	valid_0's l1: 2.45106e+06
[5]	valid_0's l1: 2.23614e+06
[6]	valid_0's l1: 2.17392e+06
[7]	valid_0's l1: 2.12559e+06
[8]	valid_0's l1: 1.99899e+06
[9]	valid_0's l1: 1.9085e+06
[10]	valid_0's l1: 1.83877e+06
[11]	valid_0's l1: 1.78734e+06
[12]	valid_0's l1: 1.75899e+06
[13]	valid_0's l1: 1.71648e+06
[14]	valid_0's l1: 1.71539e+06
[15]	valid_0's l1: 1.68911e+06
[16]	valid_0's l1: 1.67195e+06
[17]	valid_0's l1: 1.65462e+06
[18]	valid_0's l1: 1.65416e+06
[19]	valid_0's l1: 1.65014e+06
[20]	valid_0's l1: 1.64412e+06
[21]	valid_0's l1: 1.6371e+06
[22]	valid_0's l1: 1.63928e+06
[23]	valid_0's l1: 1.63282e+06
[24]	valid_0's l1: 1.63717e+06
[25]	valid_0's l1: 1.63757e+06
[26]	valid_0's l1: 1.63509e+06
[27]	valid_0's l1: 1.63896e+06
[28]	valid_0's l1: 1.63966e+06
[29]	valid_0's l1: 1.6405e+06
[30]	valid_0's l1: 1.64241e+06
[31]	valid_0's l1: 1.64361e+06
[32]	valid_0's l1: 1.64613e+06
[33]	valid_0's l1: 1.64798e+06
[34]	valid_0's l1: 1.64872e+06
[35]	valid_0's l1: 1.64828e+06
[36]	valid_0's l1: 1.64506e+06
[37]	valid_0's l1: 1.64929e+06
[38]	valid_0's l1: 1.64905e+06
[39]	valid_0's l1: 1.65143e+06
[40]	valid_0's l1: 1.64509e+06
[41]	valid_0's l1: 1.64443e+06
[42]	valid_0's l1: 1.64504e+06
[43]	valid_0's l1: 1.64629e+06
[44]	valid_0's l1: 1.64587e+06
[45]	valid_0's l1: 1.64659e+06
[46]	valid_0's l1: 1.6472e+06
[47]	valid_0's l1: 1.65008e+06
[48]	valid_0's l1: 1.65641e+06
[49]	valid_0's l1: 1.65651e+06
[50]	valid_0's l1: 1.65755e+06
[51]	valid_0's l1: 1.65789e+06
[52]	valid_0's l1: 1.65927e+06
[53]	valid_0's l1: 1.65914e+06
Early stopping, best iteration is:
[23]	valid_0's l1: 1.63282e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7301e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1745e+06
[3]	valid_0's l1: 2.77688e+06
[4]	valid_0's l1: 2.47445e+06
[5]	valid_0's l1: 2.26323e+06
[6]	valid_0's l1: 2.20126e+06
[7]	valid_0's l1: 2.15119e+06
[8]	valid_0's l1: 2.01153e+06
[9]	valid_0's l1: 1.90874e+06
[10]	valid_0's l1: 1.84571e+06
[11]	valid_0's l1: 1.78861e+06
[12]	valid_0's l1: 1.77501e+06
[13]	valid_0's l1: 1.7415e+06
[14]	valid_0's l1: 1.73695e+06
[15]	valid_0's l1: 1.71664e+06
[16]	valid_0's l1: 1.70057e+06
[17]	valid_0's l1: 1.68575e+06
[18]	valid_0's l1: 1.68101e+06
[19]	valid_0's l1: 1.66905e+06
[20]	valid_0's l1: 1.66859e+06
[21]	valid_0's l1: 1.67162e+06
[22]	valid_0's l1: 1.6639e+06
[23]	valid_0's l1: 1.66392e+06
[24]	valid_0's l1: 1.65765e+06
[25]	valid_0's l1: 1.65855e+06
[26]	valid_0's l1: 1.66059e+06
[27]	valid_0's l1: 1.65435e+06
[28]	valid_0's l1: 1.65028e+06
[29]	valid_0's l1: 1.64869e+06
[30]	valid_0's l1: 1.64393e+06
[31]	valid_0's l1: 1.64521e+06
[32]	valid_0's l1: 1.6455e+06
[33]	valid_0's l1: 1.64542e+06
[34]	valid_0's l1: 1.64099e+06
[35]	valid_0's l1: 1.64512e+06
[36]	valid_0's l1: 1.64712e+06
[37]	valid_0's l1: 1.64712e+06
[38]	valid_0's l1: 1.64563e+06
[39]	valid_0's l1: 1.64968e+06
[40]	valid_0's l1: 1.65098e+06
[41]	valid_0's l1: 1.64928e+06
[42]	valid_0's l1: 1.64421e+06
[43]	valid_0's l1: 1.64426e+06
[44]	valid_0's l1: 1.64907e+06
[45]	valid_0's l1: 1.6469e+06
[46]	valid_0's l1: 1.64921e+06
[47]	valid_0's l1: 1.65081e+06
[48]	valid_0's l1: 1.65122e+06
[49]	valid_0's l1: 1.65125e+06
[50]	valid_0's l1: 1.65428e+06
[51]	valid_0's l1: 1.65118e+06
[52]	valid_0's l1: 1.6508e+06
[53]	valid_0's l1: 1.65457e+06
[54]	valid_0's l1: 1.65743e+06
[55]	valid_0's l1: 1.65928e+06
[56]	valid_0's l1: 1.65673e+06
[57]	valid_0's l1: 1.65866e+06
[58]	valid_0's l1: 1.66043e+06
[59]	valid_0's l1: 1.65911e+06
[60]	valid_0's l1: 1.65978e+06
[61]	valid_0's l1: 1.66008e+06
[62]	valid_0's l1: 1.65961e+06
[63]	valid_0's l1: 1.65945e+06
[64]	valid_0's l1: 1.66602e+06
Early stopping, best iteration is:
[34]	valid_0's l1: 1.64099e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.68661e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1591e+06
[3]	valid_0's l1: 2.75499e+06
[4]	valid_0's l1: 2.45416e+06
[5]	valid_0's l1: 2.23723e+06
[6]	valid_0's l1: 2.1592e+06
[7]	valid_0's l1: 2.10718e+06
[8]	valid_0's l1: 1.98413e+06
[9]	valid_0's l1: 1.89977e+06
[10]	valid_0's l1: 1.83449e+06
[11]	valid_0's l1: 1.78458e+06
[12]	valid_0's l1: 1.76969e+06
[13]	valid_0's l1: 1.73441e+06
[14]	valid_0's l1: 1.73006e+06
[15]	valid_0's l1: 1.7097e+06
[16]	valid_0's l1: 1.69813e+06
[17]	valid_0's l1: 1.69385e+06
[18]	valid_0's l1: 1.67542e+06
[19]	valid_0's l1: 1.66869e+06
[20]	valid_0's l1: 1.66645e+06
[21]	valid_0's l1: 1.66198e+06
[22]	valid_0's l1: 1.663e+06
[23]	valid_0's l1: 1.65616e+06
[24]	valid_0's l1: 1.65922e+06
[25]	valid_0's l1: 1.65335e+06
[26]	valid_0's l1: 1.6563e+06
[27]	valid_0's l1: 1.65191e+06
[28]	valid_0's l1: 1.65176e+06
[29]	valid_0's l1: 1.6513e+06
[30]	valid_0's l1: 1.64843e+06
[31]	valid_0's l1: 1.65164e+06
[32]	valid_0's l1: 1.64712e+06
[33]	valid_0's l1: 1.64766e+06
[34]	valid_0's l1: 1.6514e+06
[35]	valid_0's l1: 1.65158e+06
[36]	valid_0's l1: 1.65444e+06
[37]	valid_0's l1: 1.6581e+06
[38]	valid_0's l1: 1.65599e+06
[39]	valid_0's l1: 1.65938e+06
[40]	valid_0's l1: 1.66228e+06
[41]	valid_0's l1: 1.66307e+06
[42]	valid_0's l1: 1.66281e+06
[43]	valid_0's l1: 1.66354e+06
[44]	valid_0's l1: 1.6595e+06
[45]	valid_0's l1: 1.66067e+06
[46]	valid_0's l1: 1.65911e+06
[47]	valid_0's l1: 1.66115e+06
[48]	valid_0's l1: 1.65837e+06
[49]	valid_0's l1: 1.65968e+06
[50]	valid_0's l1: 1.65673e+06
[51]	valid_0's l1: 1.65973e+06
[52]	valid_0's l1: 1.6606e+06
[53]	valid_0's l1: 1.6596e+06
[54]	valid_0's l1: 1.66112e+06
[55]	valid_0's l1: 1.65963e+06
[56]	valid_0's l1: 1.66089e+06
[57]	valid_0's l1: 1.65919e+06
[58]	valid_0's l1: 1.6567e+06
[59]	valid_0's l1: 1.65635e+06
[60]	valid_0's l1: 1.65687e+06
[61]	valid_0's l1: 1.65557e+06
[62]	valid_0's l1: 1.65768e+06
Early stopping, best iteration is:
[32]	valid_0's l1: 1.64712e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.75296e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.19259e+06
[3]	valid_0's l1: 2.7636e+06
[4]	valid_0's l1: 2.45106e+06
[5]	valid_0's l1: 2.23614e+06
[6]	valid_0's l1: 2.17392e+06
[7]	valid_0's l1: 2.12559e+06
[8]	valid_0's l1: 1.99899e+06
[9]	valid_0's l1: 1.9085e+06
[10]	valid_0's l1: 1.83877e+06
[11]	valid_0's l1: 1.78734e+06
[12]	valid_0's l1: 1.75899e+06
[13]	valid_0's l1: 1.71648e+06
[14]	valid_0's l1: 1.71539e+06
[15]	valid_0's l1: 1.68911e+06
[16]	valid_0's l1: 1.67195e+06
[17]	valid_0's l1: 1.65462e+06
[18]	valid_0's l1: 1.65416e+06
[19]	valid_0's l1: 1.65014e+06
[20]	valid_0's l1: 1.64412e+06
[21]	valid_0's l1: 1.6371e+06
[22]	valid_0's l1: 1.63928e+06
[23]	valid_0's l1: 1.63282e+06
[24]	valid_0's l1: 1.63717e+06
[25]	valid_0's l1: 1.63757e+06
[26]	valid_0's l1: 1.63509e+06
[27]	valid_0's l1: 1.63896e+06
[28]	valid_0's l1: 1.63966e+06
[29]	valid_0's l1: 1.6405e+06
[30]	valid_0's l1: 1.64241e+06
[31]	valid_0's l1: 1.64361e+06
[32]	valid_0's l1: 1.64613e+06
[33]	valid_0's l1: 1.64798e+06
[34]	valid_0's l1: 1.64872e+06
[35]	valid_0's l1: 1.64828e+06
[36]	valid_0's l1: 1.64506e+06
[37]	valid_0's l1: 1.64929e+06
[38]	valid_0's l1: 1.64905e+06
[39]	valid_0's l1: 1.65143e+06
[40]	valid_0's l1: 1.64509e+06
[41]	valid_0's l1: 1.64443e+06
[42]	valid_0's l1: 1.64504e+06
[43]	valid_0's l1: 1.64629e+06
[44]	valid_0's l1: 1.64587e+06
[45]	valid_0's l1: 1.64659e+06
[46]	valid_0's l1: 1.6472e+06
[47]	valid_0's l1: 1.65008e+06
[48]	valid_0's l1: 1.65641e+06
[49]	valid_0's l1: 1.65651e+06
[50]	valid_0's l1: 1.65755e+06
[51]	valid_0's l1: 1.65789e+06
[52]	valid_0's l1: 1.65927e+06
[53]	valid_0's l1: 1.65914e+06
Early stopping, best iteration is:
[23]	valid_0's l1: 1.63282e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7301e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1745e+06
[3]	valid_0's l1: 2.77688e+06
[4]	valid_0's l1: 2.47445e+06
[5]	valid_0's l1: 2.26323e+06
[6]	valid_0's l1: 2.20126e+06
[7]	valid_0's l1: 2.15119e+06
[8]	valid_0's l1: 2.01153e+06
[9]	valid_0's l1: 1.90874e+06
[10]	valid_0's l1: 1.84571e+06
[11]	valid_0's l1: 1.78861e+06
[12]	valid_0's l1: 1.77501e+06
[13]	valid_0's l1: 1.7415e+06
[14]	valid_0's l1: 1.73695e+06
[15]	valid_0's l1: 1.71664e+06
[16]	valid_0's l1: 1.70057e+06
[17]	valid_0's l1: 1.68575e+06
[18]	valid_0's l1: 1.68101e+06
[19]	valid_0's l1: 1.66905e+06
[20]	valid_0's l1: 1.66859e+06
[21]	valid_0's l1: 1.67162e+06
[22]	valid_0's l1: 1.6639e+06
[23]	valid_0's l1: 1.66392e+06
[24]	valid_0's l1: 1.65765e+06
[25]	valid_0's l1: 1.65855e+06
[26]	valid_0's l1: 1.66059e+06
[27]	valid_0's l1: 1.65435e+06
[28]	valid_0's l1: 1.65028e+06
[29]	valid_0's l1: 1.64869e+06
[30]	valid_0's l1: 1.64393e+06
[31]	valid_0's l1: 1.64521e+06
[32]	valid_0's l1: 1.6455e+06
[33]	valid_0's l1: 1.64542e+06
[34]	valid_0's l1: 1.64099e+06
[35]	valid_0's l1: 1.64512e+06
[36]	valid_0's l1: 1.64712e+06
[37]	valid_0's l1: 1.64712e+06
[38]	valid_0's l1: 1.64563e+06
[39]	valid_0's l1: 1.64968e+06
[40]	valid_0's l1: 1.65098e+06
[41]	valid_0's l1: 1.64928e+06
[42]	valid_0's l1: 1.64421e+06
[43]	valid_0's l1: 1.64426e+06
[44]	valid_0's l1: 1.64907e+06
[45]	valid_0's l1: 1.6469e+06
[46]	valid_0's l1: 1.64921e+06
[47]	valid_0's l1: 1.65081e+06
[48]	valid_0's l1: 1.65122e+06
[49]	valid_0's l1: 1.65125e+06
[50]	valid_0's l1: 1.65428e+06
[51]	valid_0's l1: 1.65118e+06
[52]	valid_0's l1: 1.6508e+06
[53]	valid_0's l1: 1.65457e+06
[54]	valid_0's l1: 1.65743e+06
[55]	valid_0's l1: 1.65928e+06
[56]	valid_0's l1: 1.65673e+06
[57]	valid_0's l1: 1.65866e+06
[58]	valid_0's l1: 1.66043e+06
[59]	valid_0's l1: 1.65911e+06
[60]	valid_0's l1: 1.65978e+06
[61]	valid_0's l1: 1.66008e+06
[62]	valid_0's l1: 1.65961e+06
[63]	valid_0's l1: 1.65945e+06
[64]	valid_0's l1: 1.66602e+06
Early stopping, best iteration is:
[34]	valid_0's l1: 1.64099e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.68661e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1591e+06
[3]	valid_0's l1: 2.75499e+06
[4]	valid_0's l1: 2.45416e+06
[5]	valid_0's l1: 2.23723e+06
[6]	valid_0's l1: 2.1592e+06
[7]	valid_0's l1: 2.10718e+06
[8]	valid_0's l1: 1.98413e+06
[9]	valid_0's l1: 1.89977e+06
[10]	valid_0's l1: 1.83449e+06
[11]	valid_0's l1: 1.78458e+06
[12]	valid_0's l1: 1.76969e+06
[13]	valid_0's l1: 1.73441e+06
[14]	valid_0's l1: 1.73006e+06
[15]	valid_0's l1: 1.7097e+06
[16]	valid_0's l1: 1.69813e+06
[17]	valid_0's l1: 1.69385e+06
[18]	valid_0's l1: 1.67542e+06
[19]	valid_0's l1: 1.66869e+06
[20]	valid_0's l1: 1.66645e+06
[21]	valid_0's l1: 1.66198e+06
[22]	valid_0's l1: 1.663e+06
[23]	valid_0's l1: 1.65616e+06
[24]	valid_0's l1: 1.65922e+06
[25]	valid_0's l1: 1.65335e+06
[26]	valid_0's l1: 1.6563e+06
[27]	valid_0's l1: 1.65191e+06
[28]	valid_0's l1: 1.65176e+06
[29]	valid_0's l1: 1.6513e+06
[30]	valid_0's l1: 1.64843e+06
[31]	valid_0's l1: 1.65164e+06
[32]	valid_0's l1: 1.64712e+06
[33]	valid_0's l1: 1.64766e+06
[34]	valid_0's l1: 1.6514e+06
[35]	valid_0's l1: 1.65158e+06
[36]	valid_0's l1: 1.65444e+06
[37]	valid_0's l1: 1.6581e+06
[38]	valid_0's l1: 1.65599e+06
[39]	valid_0's l1: 1.65938e+06
[40]	valid_0's l1: 1.66228e+06
[41]	valid_0's l1: 1.66307e+06
[42]	valid_0's l1: 1.66281e+06
[43]	valid_0's l1: 1.66354e+06
[44]	valid_0's l1: 1.6595e+06
[45]	valid_0's l1: 1.66067e+06
[46]	valid_0's l1: 1.65911e+06
[47]	valid_0's l1: 1.66115e+06
[48]	valid_0's l1: 1.65837e+06
[49]	valid_0's l1: 1.65968e+06
[50]	valid_0's l1: 1.65673e+06
[51]	valid_0's l1: 1.65973e+06
[52]	valid_0's l1: 1.6606e+06
[53]	valid_0's l1: 1.6596e+06
[54]	valid_0's l1: 1.66112e+06
[55]	valid_0's l1: 1.65963e+06
[56]	valid_0's l1: 1.66089e+06
[57]	valid_0's l1: 1.65919e+06
[58]	valid_0's l1: 1.6567e+06
[59]	valid_0's l1: 1.65635e+06
[60]	valid_0's l1: 1.65687e+06
[61]	valid_0's l1: 1.65557e+06
[62]	valid_0's l1: 1.65768e+06
Early stopping, best iteration is:
[32]	valid_0's l1: 1.64712e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.75296e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.19259e+06
[3]	valid_0's l1: 2.7636e+06
[4]	valid_0's l1: 2.45106e+06
[5]	valid_0's l1: 2.23614e+06
[6]	valid_0's l1: 2.17392e+06
[7]	valid_0's l1: 2.12559e+06
[8]	valid_0's l1: 1.99899e+06
[9]	valid_0's l1: 1.9085e+06
[10]	valid_0's l1: 1.83877e+06
[11]	valid_0's l1: 1.78734e+06
[12]	valid_0's l1: 1.75899e+06
[13]	valid_0's l1: 1.71648e+06
[14]	valid_0's l1: 1.71539e+06
[15]	valid_0's l1: 1.68911e+06
[16]	valid_0's l1: 1.67195e+06
[17]	valid_0's l1: 1.65462e+06
[18]	valid_0's l1: 1.65416e+06
[19]	valid_0's l1: 1.65014e+06
[20]	valid_0's l1: 1.64412e+06
[21]	valid_0's l1: 1.6371e+06
[22]	valid_0's l1: 1.63928e+06
[23]	valid_0's l1: 1.63282e+06
[24]	valid_0's l1: 1.63717e+06
[25]	valid_0's l1: 1.63757e+06
[26]	valid_0's l1: 1.63509e+06
[27]	valid_0's l1: 1.63896e+06
[28]	valid_0's l1: 1.63966e+06
[29]	valid_0's l1: 1.6405e+06
[30]	valid_0's l1: 1.64241e+06
[31]	valid_0's l1: 1.64361e+06
[32]	valid_0's l1: 1.64613e+06
[33]	valid_0's l1: 1.64798e+06
[34]	valid_0's l1: 1.64872e+06
[35]	valid_0's l1: 1.64828e+06
[36]	valid_0's l1: 1.64506e+06
[37]	valid_0's l1: 1.64929e+06
[38]	valid_0's l1: 1.64905e+06
[39]	valid_0's l1: 1.65143e+06
[40]	valid_0's l1: 1.64509e+06
[41]	valid_0's l1: 1.64443e+06
[42]	valid_0's l1: 1.64504e+06
[43]	valid_0's l1: 1.64629e+06
[44]	valid_0's l1: 1.64587e+06
[45]	valid_0's l1: 1.64659e+06
[46]	valid_0's l1: 1.6472e+06
[47]	valid_0's l1: 1.65008e+06
[48]	valid_0's l1: 1.65641e+06
[49]	valid_0's l1: 1.65651e+06
[50]	valid_0's l1: 1.65755e+06
[51]	valid_0's l1: 1.65789e+06
[52]	valid_0's l1: 1.65927e+06
[53]	valid_0's l1: 1.65914e+06
Early stopping, best iteration is:
[23]	valid_0's l1: 1.63282e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7301e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1745e+06
[3]	valid_0's l1: 2.77688e+06
[4]	valid_0's l1: 2.47445e+06
[5]	valid_0's l1: 2.26323e+06
[6]	valid_0's l1: 2.20126e+06
[7]	valid_0's l1: 2.15119e+06
[8]	valid_0's l1: 2.01153e+06
[9]	valid_0's l1: 1.90874e+06
[10]	valid_0's l1: 1.84571e+06
[11]	valid_0's l1: 1.78861e+06
[12]	valid_0's l1: 1.77501e+06
[13]	valid_0's l1: 1.7415e+06
[14]	valid_0's l1: 1.73695e+06
[15]	valid_0's l1: 1.71664e+06
[16]	valid_0's l1: 1.70057e+06
[17]	valid_0's l1: 1.68575e+06
[18]	valid_0's l1: 1.68101e+06
[19]	valid_0's l1: 1.66905e+06
[20]	valid_0's l1: 1.66859e+06
[21]	valid_0's l1: 1.67162e+06
[22]	valid_0's l1: 1.6639e+06
[23]	valid_0's l1: 1.66392e+06
[24]	valid_0's l1: 1.65765e+06
[25]	valid_0's l1: 1.65855e+06
[26]	valid_0's l1: 1.66059e+06
[27]	valid_0's l1: 1.65435e+06
[28]	valid_0's l1: 1.65028e+06
[29]	valid_0's l1: 1.64869e+06
[30]	valid_0's l1: 1.64393e+06
[31]	valid_0's l1: 1.64521e+06
[32]	valid_0's l1: 1.6455e+06
[33]	valid_0's l1: 1.64542e+06
[34]	valid_0's l1: 1.64099e+06
[35]	valid_0's l1: 1.64512e+06
[36]	valid_0's l1: 1.64712e+06
[37]	valid_0's l1: 1.64712e+06
[38]	valid_0's l1: 1.64563e+06
[39]	valid_0's l1: 1.64968e+06
[40]	valid_0's l1: 1.65098e+06
[41]	valid_0's l1: 1.64928e+06
[42]	valid_0's l1: 1.64421e+06
[43]	valid_0's l1: 1.64426e+06
[44]	valid_0's l1: 1.64907e+06
[45]	valid_0's l1: 1.6469e+06
[46]	valid_0's l1: 1.64921e+06
[47]	valid_0's l1: 1.65081e+06
[48]	valid_0's l1: 1.65122e+06
[49]	valid_0's l1: 1.65125e+06
[50]	valid_0's l1: 1.65428e+06
[51]	valid_0's l1: 1.65118e+06
[52]	valid_0's l1: 1.6508e+06
[53]	valid_0's l1: 1.65457e+06
[54]	valid_0's l1: 1.65743e+06
[55]	valid_0's l1: 1.65928e+06
[56]	valid_0's l1: 1.65673e+06
[57]	valid_0's l1: 1.65866e+06
[58]	valid_0's l1: 1.66043e+06
[59]	valid_0's l1: 1.65911e+06
[60]	valid_0's l1: 1.65978e+06
[61]	valid_0's l1: 1.66008e+06
[62]	valid_0's l1: 1.65961e+06
[63]	valid_0's l1: 1.65945e+06
[64]	valid_0's l1: 1.66602e+06
Early stopping, best iteration is:
[34]	valid_0's l1: 1.64099e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.68661e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1591e+06
[3]	valid_0's l1: 2.75499e+06
[4]	valid_0's l1: 2.45416e+06
[5]	valid_0's l1: 2.23723e+06
[6]	valid_0's l1: 2.1592e+06
[7]	valid_0's l1: 2.10718e+06
[8]	valid_0's l1: 1.98413e+06
[9]	valid_0's l1: 1.89977e+06
[10]	valid_0's l1: 1.83449e+06
[11]	valid_0's l1: 1.78458e+06
[12]	valid_0's l1: 1.76969e+06
[13]	valid_0's l1: 1.73441e+06
[14]	valid_0's l1: 1.73006e+06
[15]	valid_0's l1: 1.7097e+06
[16]	valid_0's l1: 1.69813e+06
[17]	valid_0's l1: 1.69385e+06
[18]	valid_0's l1: 1.67542e+06
[19]	valid_0's l1: 1.66869e+06
[20]	valid_0's l1: 1.66645e+06
[21]	valid_0's l1: 1.66198e+06
[22]	valid_0's l1: 1.663e+06
[23]	valid_0's l1: 1.65616e+06
[24]	valid_0's l1: 1.65922e+06
[25]	valid_0's l1: 1.65335e+06
[26]	valid_0's l1: 1.6563e+06
[27]	valid_0's l1: 1.65191e+06
[28]	valid_0's l1: 1.65176e+06
[29]	valid_0's l1: 1.6513e+06
[30]	valid_0's l1: 1.64843e+06
[31]	valid_0's l1: 1.65164e+06
[32]	valid_0's l1: 1.64712e+06
[33]	valid_0's l1: 1.64766e+06
[34]	valid_0's l1: 1.6514e+06
[35]	valid_0's l1: 1.65158e+06
[36]	valid_0's l1: 1.65444e+06
[37]	valid_0's l1: 1.6581e+06
[38]	valid_0's l1: 1.65599e+06
[39]	valid_0's l1: 1.65938e+06
[40]	valid_0's l1: 1.66228e+06
[41]	valid_0's l1: 1.66307e+06
[42]	valid_0's l1: 1.66281e+06
[43]	valid_0's l1: 1.66354e+06
[44]	valid_0's l1: 1.6595e+06
[45]	valid_0's l1: 1.66067e+06
[46]	valid_0's l1: 1.65911e+06
[47]	valid_0's l1: 1.66115e+06
[48]	valid_0's l1: 1.65837e+06
[49]	valid_0's l1: 1.65968e+06
[50]	valid_0's l1: 1.65673e+06
[51]	valid_0's l1: 1.65973e+06
[52]	valid_0's l1: 1.6606e+06
[53]	valid_0's l1: 1.6596e+06
[54]	valid_0's l1: 1.66112e+06
[55]	valid_0's l1: 1.65963e+06
[56]	valid_0's l1: 1.66089e+06
[57]	valid_0's l1: 1.65919e+06
[58]	valid_0's l1: 1.6567e+06
[59]	valid_0's l1: 1.65635e+06
[60]	valid_0's l1: 1.65687e+06
[61]	valid_0's l1: 1.65557e+06
[62]	valid_0's l1: 1.65768e+06
Early stopping, best iteration is:
[32]	valid_0's l1: 1.64712e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.75296e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.19259e+06
[3]	valid_0's l1: 2.7636e+06
[4]	valid_0's l1: 2.45106e+06
[5]	valid_0's l1: 2.23614e+06
[6]	valid_0's l1: 2.17392e+06
[7]	valid_0's l1: 2.12559e+06
[8]	valid_0's l1: 1.99899e+06
[9]	valid_0's l1: 1.9085e+06
[10]	valid_0's l1: 1.83877e+06
[11]	valid_0's l1: 1.78734e+06
[12]	valid_0's l1: 1.75899e+06
[13]	valid_0's l1: 1.71648e+06
[14]	valid_0's l1: 1.71539e+06
[15]	valid_0's l1: 1.68911e+06
[16]	valid_0's l1: 1.67195e+06
[17]	valid_0's l1: 1.65462e+06
[18]	valid_0's l1: 1.65416e+06
[19]	valid_0's l1: 1.65014e+06
[20]	valid_0's l1: 1.64412e+06
[21]	valid_0's l1: 1.6371e+06
[22]	valid_0's l1: 1.63928e+06
[23]	valid_0's l1: 1.63282e+06
[24]	valid_0's l1: 1.63717e+06
[25]	valid_0's l1: 1.63757e+06
[26]	valid_0's l1: 1.63509e+06
[27]	valid_0's l1: 1.63896e+06
[28]	valid_0's l1: 1.63966e+06
[29]	valid_0's l1: 1.6405e+06
[30]	valid_0's l1: 1.64241e+06
[31]	valid_0's l1: 1.64361e+06
[32]	valid_0's l1: 1.64613e+06
[33]	valid_0's l1: 1.64798e+06
[34]	valid_0's l1: 1.64872e+06
[35]	valid_0's l1: 1.64828e+06
[36]	valid_0's l1: 1.64506e+06
[37]	valid_0's l1: 1.64929e+06
[38]	valid_0's l1: 1.64905e+06
[39]	valid_0's l1: 1.65143e+06
[40]	valid_0's l1: 1.64509e+06
[41]	valid_0's l1: 1.64443e+06
[42]	valid_0's l1: 1.64504e+06
[43]	valid_0's l1: 1.64629e+06
[44]	valid_0's l1: 1.64587e+06
[45]	valid_0's l1: 1.64659e+06
[46]	valid_0's l1: 1.6472e+06
[47]	valid_0's l1: 1.65008e+06
[48]	valid_0's l1: 1.65641e+06
[49]	valid_0's l1: 1.65651e+06
[50]	valid_0's l1: 1.65755e+06
[51]	valid_0's l1: 1.65789e+06
[52]	valid_0's l1: 1.65927e+06
[53]	valid_0's l1: 1.65914e+06
Early stopping, best iteration is:
[23]	valid_0's l1: 1.63282e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7301e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1745e+06
[3]	valid_0's l1: 2.77688e+06
[4]	valid_0's l1: 2.47445e+06
[5]	valid_0's l1: 2.26323e+06
[6]	valid_0's l1: 2.20126e+06
[7]	valid_0's l1: 2.15119e+06
[8]	valid_0's l1: 2.01153e+06
[9]	valid_0's l1: 1.90874e+06
[10]	valid_0's l1: 1.84571e+06
[11]	valid_0's l1: 1.78861e+06
[12]	valid_0's l1: 1.77501e+06
[13]	valid_0's l1: 1.7415e+06
[14]	valid_0's l1: 1.73695e+06
[15]	valid_0's l1: 1.71664e+06
[16]	valid_0's l1: 1.70057e+06
[17]	valid_0's l1: 1.68575e+06
[18]	valid_0's l1: 1.68101e+06
[19]	valid_0's l1: 1.66905e+06
[20]	valid_0's l1: 1.66859e+06
[21]	valid_0's l1: 1.67162e+06
[22]	valid_0's l1: 1.6639e+06
[23]	valid_0's l1: 1.66392e+06
[24]	valid_0's l1: 1.65765e+06
[25]	valid_0's l1: 1.65855e+06
[26]	valid_0's l1: 1.66059e+06
[27]	valid_0's l1: 1.65435e+06
[28]	valid_0's l1: 1.65028e+06
[29]	valid_0's l1: 1.64869e+06
[30]	valid_0's l1: 1.64393e+06
[31]	valid_0's l1: 1.64521e+06
[32]	valid_0's l1: 1.6455e+06
[33]	valid_0's l1: 1.64542e+06
[34]	valid_0's l1: 1.64099e+06
[35]	valid_0's l1: 1.64512e+06
[36]	valid_0's l1: 1.64712e+06
[37]	valid_0's l1: 1.64712e+06
[38]	valid_0's l1: 1.64563e+06
[39]	valid_0's l1: 1.64968e+06
[40]	valid_0's l1: 1.65098e+06
[41]	valid_0's l1: 1.64928e+06
[42]	valid_0's l1: 1.64421e+06
[43]	valid_0's l1: 1.64426e+06
[44]	valid_0's l1: 1.64907e+06
[45]	valid_0's l1: 1.6469e+06
[46]	valid_0's l1: 1.64921e+06
[47]	valid_0's l1: 1.65081e+06
[48]	valid_0's l1: 1.65122e+06
[49]	valid_0's l1: 1.65125e+06
[50]	valid_0's l1: 1.65428e+06
[51]	valid_0's l1: 1.65118e+06
[52]	valid_0's l1: 1.6508e+06
[53]	valid_0's l1: 1.65457e+06
[54]	valid_0's l1: 1.65743e+06
[55]	valid_0's l1: 1.65928e+06
[56]	valid_0's l1: 1.65673e+06
[57]	valid_0's l1: 1.65866e+06
[58]	valid_0's l1: 1.66043e+06
[59]	valid_0's l1: 1.65911e+06
[60]	valid_0's l1: 1.65978e+06
[61]	valid_0's l1: 1.66008e+06
[62]	valid_0's l1: 1.65961e+06
[63]	valid_0's l1: 1.65945e+06
[64]	valid_0's l1: 1.66602e+06
Early stopping, best iteration is:
[34]	valid_0's l1: 1.64099e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.68661e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.1591e+06
[3]	valid_0's l1: 2.75499e+06
[4]	valid_0's l1: 2.45416e+06
[5]	valid_0's l1: 2.23723e+06
[6]	valid_0's l1: 2.1592e+06
[7]	valid_0's l1: 2.10718e+06
[8]	valid_0's l1: 1.98413e+06
[9]	valid_0's l1: 1.89977e+06
[10]	valid_0's l1: 1.83449e+06
[11]	valid_0's l1: 1.78458e+06
[12]	valid_0's l1: 1.76969e+06
[13]	valid_0's l1: 1.73441e+06
[14]	valid_0's l1: 1.73006e+06
[15]	valid_0's l1: 1.7097e+06
[16]	valid_0's l1: 1.69813e+06
[17]	valid_0's l1: 1.69385e+06
[18]	valid_0's l1: 1.67542e+06
[19]	valid_0's l1: 1.66869e+06
[20]	valid_0's l1: 1.66645e+06
[21]	valid_0's l1: 1.66198e+06
[22]	valid_0's l1: 1.663e+06
[23]	valid_0's l1: 1.65616e+06
[24]	valid_0's l1: 1.65922e+06
[25]	valid_0's l1: 1.65335e+06
[26]	valid_0's l1: 1.6563e+06
[27]	valid_0's l1: 1.65191e+06
[28]	valid_0's l1: 1.65176e+06
[29]	valid_0's l1: 1.6513e+06
[30]	valid_0's l1: 1.64843e+06
[31]	valid_0's l1: 1.65164e+06
[32]	valid_0's l1: 1.64712e+06
[33]	valid_0's l1: 1.64766e+06
[34]	valid_0's l1: 1.6514e+06
[35]	valid_0's l1: 1.65158e+06
[36]	valid_0's l1: 1.65444e+06
[37]	valid_0's l1: 1.6581e+06
[38]	valid_0's l1: 1.65599e+06
[39]	valid_0's l1: 1.65938e+06
[40]	valid_0's l1: 1.66228e+06
[41]	valid_0's l1: 1.66307e+06
[42]	valid_0's l1: 1.66281e+06
[43]	valid_0's l1: 1.66354e+06
[44]	valid_0's l1: 1.6595e+06
[45]	valid_0's l1: 1.66067e+06
[46]	valid_0's l1: 1.65911e+06
[47]	valid_0's l1: 1.66115e+06
[48]	valid_0's l1: 1.65837e+06
[49]	valid_0's l1: 1.65968e+06
[50]	valid_0's l1: 1.65673e+06
[51]	valid_0's l1: 1.65973e+06
[52]	valid_0's l1: 1.6606e+06
[53]	valid_0's l1: 1.6596e+06
[54]	valid_0's l1: 1.66112e+06
[55]	valid_0's l1: 1.65963e+06
[56]	valid_0's l1: 1.66089e+06
[57]	valid_0's l1: 1.65919e+06
[58]	valid_0's l1: 1.6567e+06
[59]	valid_0's l1: 1.65635e+06
[60]	valid_0's l1: 1.65687e+06
[61]	valid_0's l1: 1.65557e+06
[62]	valid_0's l1: 1.65768e+06
Early stopping, best iteration is:
[32]	valid_0's l1: 1.64712e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.75296e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.19259e+06
[3]	valid_0's l1: 2.7636e+06
[4]	valid_0's l1: 2.45106e+06
[5]	valid_0's l1: 2.23614e+06
[6]	valid_0's l1: 2.17392e+06
[7]	valid_0's l1: 2.12559e+06
[8]	valid_0's l1: 1.99899e+06
[9]	valid_0's l1: 1.9085e+06
[10]	valid_0's l1: 1.83877e+06
[11]	valid_0's l1: 1.78734e+06
[12]	valid_0's l1: 1.75899e+06
[13]	valid_0's l1: 1.71648e+06
[14]	valid_0's l1: 1.71539e+06
[15]	valid_0's l1: 1.68911e+06
[16]	valid_0's l1: 1.67195e+06
[17]	valid_0's l1: 1.65462e+06
[18]	valid_0's l1: 1.65416e+06
[19]	valid_0's l1: 1.65014e+06
[20]	valid_0's l1: 1.64412e+06
[21]	valid_0's l1: 1.6371e+06
[22]	valid_0's l1: 1.63928e+06
[23]	valid_0's l1: 1.63282e+06
[24]	valid_0's l1: 1.63717e+06
[25]	valid_0's l1: 1.63757e+06
[26]	valid_0's l1: 1.63509e+06
[27]	valid_0's l1: 1.63896e+06
[28]	valid_0's l1: 1.63966e+06
[29]	valid_0's l1: 1.6405e+06
[30]	valid_0's l1: 1.64241e+06
[31]	valid_0's l1: 1.64361e+06
[32]	valid_0's l1: 1.64613e+06
[33]	valid_0's l1: 1.64798e+06
[34]	valid_0's l1: 1.64872e+06
[35]	valid_0's l1: 1.64828e+06
[36]	valid_0's l1: 1.64506e+06
[37]	valid_0's l1: 1.64929e+06
[38]	valid_0's l1: 1.64905e+06
[39]	valid_0's l1: 1.65143e+06
[40]	valid_0's l1: 1.64509e+06
[41]	valid_0's l1: 1.64443e+06
[42]	valid_0's l1: 1.64504e+06
[43]	valid_0's l1: 1.64629e+06
[44]	valid_0's l1: 1.64587e+06
[45]	valid_0's l1: 1.64659e+06
[46]	valid_0's l1: 1.6472e+06
[47]	valid_0's l1: 1.65008e+06
[48]	valid_0's l1: 1.65641e+06
[49]	valid_0's l1: 1.65651e+06
[50]	valid_0's l1: 1.65755e+06
[51]	valid_0's l1: 1.65789e+06
[52]	valid_0's l1: 1.65927e+06
[53]	valid_0's l1: 1.65914e+06
Early stopping, best iteration is:
[23]	valid_0's l1: 1.63282e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7172e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17345e+06
[3]	valid_0's l1: 2.77403e+06
[4]	valid_0's l1: 2.47886e+06
[5]	valid_0's l1: 2.26288e+06
[6]	valid_0's l1: 2.19668e+06
[7]	valid_0's l1: 2.14756e+06
[8]	valid_0's l1: 2.00628e+06
[9]	valid_0's l1: 1.90309e+06
[10]	valid_0's l1: 1.84191e+06
[11]	valid_0's l1: 1.78333e+06
[12]	valid_0's l1: 1.75664e+06
[13]	valid_0's l1: 1.72714e+06
[14]	valid_0's l1: 1.72713e+06
[15]	valid_0's l1: 1.70508e+06
[16]	valid_0's l1: 1.68751e+06
[17]	valid_0's l1: 1.67159e+06
[18]	valid_0's l1: 1.66508e+06
[19]	valid_0's l1: 1.66682e+06
[20]	valid_0's l1: 1.65486e+06
[21]	valid_0's l1: 1.65807e+06
[22]	valid_0's l1: 1.65513e+06
[23]	valid_0's l1: 1.65293e+06
[24]	valid_0's l1: 1.65676e+06
[25]	valid_0's l1: 1.6567e+06
[26]	valid_0's l1: 1.65246e+06
[27]	valid_0's l1: 1.65489e+06
[28]	valid_0's l1: 1.6542e+06
[29]	valid_0's l1: 1.65756e+06
[30]	valid_0's l1: 1.64798e+06
[31]	valid_0's l1: 1.64311e+06
[32]	valid_0's l1: 1.64597e+06
[33]	valid_0's l1: 1.6487e+06
[34]	valid_0's l1: 1.65293e+06
[35]	valid_0's l1: 1.65345e+06
[36]	valid_0's l1: 1.65514e+06
[37]	valid_0's l1: 1.65351e+06
[38]	valid_0's l1: 1.65272e+06
[39]	valid_0's l1: 1.65673e+06
[40]	valid_0's l1: 1.65663e+06
[41]	valid_0's l1: 1.65784e+06
[42]	valid_0's l1: 1.65672e+06
[43]	valid_0's l1: 1.65752e+06
[44]	valid_0's l1: 1.65753e+06
[45]	valid_0's l1: 1.65528e+06
[46]	valid_0's l1: 1.66035e+06
[47]	valid_0's l1: 1.66167e+06
[48]	valid_0's l1: 1.66245e+06
[49]	valid_0's l1: 1.66084e+06
[50]	valid_0's l1: 1.66428e+06
[51]	valid_0's l1: 1.66446e+06
[52]	valid_0's l1: 1.66727e+06
[53]	valid_0's l1: 1.67062e+06
[54]	valid_0's l1: 1.67354e+06
[55]	valid_0's l1: 1.67543e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67716e+06
[58]	valid_0's l1: 1.67859e+06
[59]	valid_0's l1: 1.68064e+06
[60]	valid_0's l1: 1.68223e+06
[61]	valid_0's l1: 1.68239e+06
Early stopping, best iteration is:
[31]	valid_0's l1: 1.64311e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.67303e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.15957e+06
[3]	valid_0's l1: 2.74986e+06
[4]	valid_0's l1: 2.45151e+06
[5]	valid_0's l1: 2.23013e+06
[6]	valid_0's l1: 2.15413e+06
[7]	valid_0's l1: 2.08852e+06
[8]	valid_0's l1: 1.97426e+06
[9]	valid_0's l1: 1.88784e+06
[10]	valid_0's l1: 1.82639e+06
[11]	valid_0's l1: 1.77641e+06
[12]	valid_0's l1: 1.7611e+06
[13]	valid_0's l1: 1.7281e+06
[14]	valid_0's l1: 1.71859e+06
[15]	valid_0's l1: 1.69797e+06
[16]	valid_0's l1: 1.68329e+06
[17]	valid_0's l1: 1.68038e+06
[18]	valid_0's l1: 1.66907e+06
[19]	valid_0's l1: 1.66621e+06
[20]	valid_0's l1: 1.66287e+06
[21]	valid_0's l1: 1.66018e+06
[22]	valid_0's l1: 1.66398e+06
[23]	valid_0's l1: 1.66027e+06
[24]	valid_0's l1: 1.66435e+06
[25]	valid_0's l1: 1.65992e+06
[26]	valid_0's l1: 1.66286e+06
[27]	valid_0's l1: 1.65973e+06
[28]	valid_0's l1: 1.65974e+06
[29]	valid_0's l1: 1.6571e+06
[30]	valid_0's l1: 1.65502e+06
[31]	valid_0's l1: 1.65876e+06
[32]	valid_0's l1: 1.66014e+06
[33]	valid_0's l1: 1.6561e+06
[34]	valid_0's l1: 1.65872e+06
[35]	valid_0's l1: 1.65888e+06
[36]	valid_0's l1: 1.65659e+06
[37]	valid_0's l1: 1.65984e+06
[38]	valid_0's l1: 1.65935e+06
[39]	valid_0's l1: 1.6611e+06
[40]	valid_0's l1: 1.66236e+06
[41]	valid_0's l1: 1.65998e+06
[42]	valid_0's l1: 1.66392e+06
[43]	valid_0's l1: 1.66179e+06
[44]	valid_0's l1: 1.66272e+06
[45]	valid_0's l1: 1.66274e+06
[46]	valid_0's l1: 1.66192e+06
[47]	valid_0's l1: 1.66486e+06
[48]	valid_0's l1: 1.66293e+06
[49]	valid_0's l1: 1.6636e+06
[50]	valid_0's l1: 1.66386e+06
[51]	valid_0's l1: 1.66824e+06
[52]	valid_0's l1: 1.66677e+06
[53]	valid_0's l1: 1.67165e+06
[54]	valid_0's l1: 1.67538e+06
[55]	valid_0's l1: 1.67742e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67701e+06
[58]	valid_0's l1: 1.67817e+06
[59]	valid_0's l1: 1.67647e+06
[60]	valid_0's l1: 1.67678e+06
Early stopping, best iteration is:
[30]	valid_0's l1: 1.65502e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.74198e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17925e+06
[3]	valid_0's l1: 2.75493e+06
[4]	valid_0's l1: 2.43331e+06
[5]	valid_0's l1: 2.21332e+06
[6]	valid_0's l1: 2.1413e+06
[7]	valid_0's l1: 2.09055e+06
[8]	valid_0's l1: 1.97663e+06
[9]	valid_0's l1: 1.88299e+06
[10]	valid_0's l1: 1.81844e+06
[11]	valid_0's l1: 1.76375e+06
[12]	valid_0's l1: 1.74997e+06
[13]	valid_0's l1: 1.71063e+06
[14]	valid_0's l1: 1.70095e+06
[15]	valid_0's l1: 1.68101e+06
[16]	valid_0's l1: 1.6596e+06
[17]	valid_0's l1: 1.65919e+06
[18]	valid_0's l1: 1.64736e+06
[19]	valid_0's l1: 1.64521e+06
[20]	valid_0's l1: 1.64499e+06
[21]	valid_0's l1: 1.63518e+06
[22]	valid_0's l1: 1.63929e+06
[23]	valid_0's l1: 1.64545e+06
[24]	valid_0's l1: 1.64718e+06
[25]	valid_0's l1: 1.64141e+06
[26]	valid_0's l1: 1.64456e+06
[27]	valid_0's l1: 1.64418e+06
[28]	valid_0's l1: 1.64485e+06
[29]	valid_0's l1: 1.65057e+06
[30]	valid_0's l1: 1.65105e+06
[31]	valid_0's l1: 1.65194e+06
[32]	valid_0's l1: 1.65609e+06
[33]	valid_0's l1: 1.65301e+06
[34]	valid_0's l1: 1.65495e+06
[35]	valid_0's l1: 1.65622e+06
[36]	valid_0's l1: 1.66002e+06
[37]	valid_0's l1: 1.66264e+06
[38]	valid_0's l1: 1.66355e+06
[39]	valid_0's l1: 1.66487e+06
[40]	valid_0's l1: 1.66699e+06
[41]	valid_0's l1: 1.66554e+06
[42]	valid_0's l1: 1.66476e+06
[43]	valid_0's l1: 1.66452e+06
[44]	valid_0's l1: 1.66608e+06
[45]	valid_0's l1: 1.66929e+06
[46]	valid_0's l1: 1.66908e+06
[47]	valid_0's l1: 1.66932e+06
[48]	valid_0's l1: 1.66901e+06
[49]	valid_0's l1: 1.66908e+06
[50]	valid_0's l1: 1.67006e+06
[51]	valid_0's l1: 1.66873e+06
Early stopping, best iteration is:
[21]	valid_0's l1: 1.63518e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7172e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17345e+06
[3]	valid_0's l1: 2.77403e+06
[4]	valid_0's l1: 2.47886e+06
[5]	valid_0's l1: 2.26288e+06
[6]	valid_0's l1: 2.19668e+06
[7]	valid_0's l1: 2.14756e+06
[8]	valid_0's l1: 2.00628e+06
[9]	valid_0's l1: 1.90309e+06
[10]	valid_0's l1: 1.84191e+06
[11]	valid_0's l1: 1.78333e+06
[12]	valid_0's l1: 1.75664e+06
[13]	valid_0's l1: 1.72714e+06
[14]	valid_0's l1: 1.72713e+06
[15]	valid_0's l1: 1.70508e+06
[16]	valid_0's l1: 1.68751e+06
[17]	valid_0's l1: 1.67159e+06
[18]	valid_0's l1: 1.66508e+06
[19]	valid_0's l1: 1.66682e+06
[20]	valid_0's l1: 1.65486e+06
[21]	valid_0's l1: 1.65807e+06
[22]	valid_0's l1: 1.65513e+06
[23]	valid_0's l1: 1.65293e+06
[24]	valid_0's l1: 1.65676e+06
[25]	valid_0's l1: 1.6567e+06
[26]	valid_0's l1: 1.65246e+06
[27]	valid_0's l1: 1.65489e+06
[28]	valid_0's l1: 1.6542e+06
[29]	valid_0's l1: 1.65756e+06
[30]	valid_0's l1: 1.64798e+06
[31]	valid_0's l1: 1.64311e+06
[32]	valid_0's l1: 1.64597e+06
[33]	valid_0's l1: 1.6487e+06
[34]	valid_0's l1: 1.65293e+06
[35]	valid_0's l1: 1.65345e+06
[36]	valid_0's l1: 1.65514e+06
[37]	valid_0's l1: 1.65351e+06
[38]	valid_0's l1: 1.65272e+06
[39]	valid_0's l1: 1.65673e+06
[40]	valid_0's l1: 1.65663e+06
[41]	valid_0's l1: 1.65784e+06
[42]	valid_0's l1: 1.65672e+06
[43]	valid_0's l1: 1.65752e+06
[44]	valid_0's l1: 1.65753e+06
[45]	valid_0's l1: 1.65528e+06
[46]	valid_0's l1: 1.66035e+06
[47]	valid_0's l1: 1.66167e+06
[48]	valid_0's l1: 1.66245e+06
[49]	valid_0's l1: 1.66084e+06
[50]	valid_0's l1: 1.66428e+06
[51]	valid_0's l1: 1.66446e+06
[52]	valid_0's l1: 1.66727e+06
[53]	valid_0's l1: 1.67062e+06
[54]	valid_0's l1: 1.67354e+06
[55]	valid_0's l1: 1.67543e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67716e+06
[58]	valid_0's l1: 1.67859e+06
[59]	valid_0's l1: 1.68064e+06
[60]	valid_0's l1: 1.68223e+06
[61]	valid_0's l1: 1.68239e+06
Early stopping, best iteration is:
[31]	valid_0's l1: 1.64311e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.67303e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.15957e+06
[3]	valid_0's l1: 2.74986e+06
[4]	valid_0's l1: 2.45151e+06
[5]	valid_0's l1: 2.23013e+06
[6]	valid_0's l1: 2.15413e+06
[7]	valid_0's l1: 2.08852e+06
[8]	valid_0's l1: 1.97426e+06
[9]	valid_0's l1: 1.88784e+06
[10]	valid_0's l1: 1.82639e+06
[11]	valid_0's l1: 1.77641e+06
[12]	valid_0's l1: 1.7611e+06
[13]	valid_0's l1: 1.7281e+06
[14]	valid_0's l1: 1.71859e+06
[15]	valid_0's l1: 1.69797e+06
[16]	valid_0's l1: 1.68329e+06
[17]	valid_0's l1: 1.68038e+06
[18]	valid_0's l1: 1.66907e+06
[19]	valid_0's l1: 1.66621e+06
[20]	valid_0's l1: 1.66287e+06
[21]	valid_0's l1: 1.66018e+06
[22]	valid_0's l1: 1.66398e+06
[23]	valid_0's l1: 1.66027e+06
[24]	valid_0's l1: 1.66435e+06
[25]	valid_0's l1: 1.65992e+06
[26]	valid_0's l1: 1.66286e+06
[27]	valid_0's l1: 1.65973e+06
[28]	valid_0's l1: 1.65974e+06
[29]	valid_0's l1: 1.6571e+06
[30]	valid_0's l1: 1.65502e+06
[31]	valid_0's l1: 1.65876e+06
[32]	valid_0's l1: 1.66014e+06
[33]	valid_0's l1: 1.6561e+06
[34]	valid_0's l1: 1.65872e+06
[35]	valid_0's l1: 1.65888e+06
[36]	valid_0's l1: 1.65659e+06
[37]	valid_0's l1: 1.65984e+06
[38]	valid_0's l1: 1.65935e+06
[39]	valid_0's l1: 1.6611e+06
[40]	valid_0's l1: 1.66236e+06
[41]	valid_0's l1: 1.65998e+06
[42]	valid_0's l1: 1.66392e+06
[43]	valid_0's l1: 1.66179e+06
[44]	valid_0's l1: 1.66272e+06
[45]	valid_0's l1: 1.66274e+06
[46]	valid_0's l1: 1.66192e+06
[47]	valid_0's l1: 1.66486e+06
[48]	valid_0's l1: 1.66293e+06
[49]	valid_0's l1: 1.6636e+06
[50]	valid_0's l1: 1.66386e+06
[51]	valid_0's l1: 1.66824e+06
[52]	valid_0's l1: 1.66677e+06
[53]	valid_0's l1: 1.67165e+06
[54]	valid_0's l1: 1.67538e+06
[55]	valid_0's l1: 1.67742e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67701e+06
[58]	valid_0's l1: 1.67817e+06
[59]	valid_0's l1: 1.67647e+06
[60]	valid_0's l1: 1.67678e+06
Early stopping, best iteration is:
[30]	valid_0's l1: 1.65502e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.74198e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17925e+06
[3]	valid_0's l1: 2.75493e+06
[4]	valid_0's l1: 2.43331e+06
[5]	valid_0's l1: 2.21332e+06
[6]	valid_0's l1: 2.1413e+06
[7]	valid_0's l1: 2.09055e+06
[8]	valid_0's l1: 1.97663e+06
[9]	valid_0's l1: 1.88299e+06
[10]	valid_0's l1: 1.81844e+06
[11]	valid_0's l1: 1.76375e+06
[12]	valid_0's l1: 1.74997e+06
[13]	valid_0's l1: 1.71063e+06
[14]	valid_0's l1: 1.70095e+06
[15]	valid_0's l1: 1.68101e+06
[16]	valid_0's l1: 1.6596e+06
[17]	valid_0's l1: 1.65919e+06
[18]	valid_0's l1: 1.64736e+06
[19]	valid_0's l1: 1.64521e+06
[20]	valid_0's l1: 1.64499e+06
[21]	valid_0's l1: 1.63518e+06
[22]	valid_0's l1: 1.63929e+06
[23]	valid_0's l1: 1.64545e+06
[24]	valid_0's l1: 1.64718e+06
[25]	valid_0's l1: 1.64141e+06
[26]	valid_0's l1: 1.64456e+06
[27]	valid_0's l1: 1.64418e+06
[28]	valid_0's l1: 1.64485e+06
[29]	valid_0's l1: 1.65057e+06
[30]	valid_0's l1: 1.65105e+06
[31]	valid_0's l1: 1.65194e+06
[32]	valid_0's l1: 1.65609e+06
[33]	valid_0's l1: 1.65301e+06
[34]	valid_0's l1: 1.65495e+06
[35]	valid_0's l1: 1.65622e+06
[36]	valid_0's l1: 1.66002e+06
[37]	valid_0's l1: 1.66264e+06
[38]	valid_0's l1: 1.66355e+06
[39]	valid_0's l1: 1.66487e+06
[40]	valid_0's l1: 1.66699e+06
[41]	valid_0's l1: 1.66554e+06
[42]	valid_0's l1: 1.66476e+06
[43]	valid_0's l1: 1.66452e+06
[44]	valid_0's l1: 1.66608e+06
[45]	valid_0's l1: 1.66929e+06
[46]	valid_0's l1: 1.66908e+06
[47]	valid_0's l1: 1.66932e+06
[48]	valid_0's l1: 1.66901e+06
[49]	valid_0's l1: 1.66908e+06
[50]	valid_0's l1: 1.67006e+06
[51]	valid_0's l1: 1.66873e+06
Early stopping, best iteration is:
[21]	valid_0's l1: 1.63518e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7172e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17345e+06
[3]	valid_0's l1: 2.77403e+06
[4]	valid_0's l1: 2.47886e+06
[5]	valid_0's l1: 2.26288e+06
[6]	valid_0's l1: 2.19668e+06
[7]	valid_0's l1: 2.14756e+06
[8]	valid_0's l1: 2.00628e+06
[9]	valid_0's l1: 1.90309e+06
[10]	valid_0's l1: 1.84191e+06
[11]	valid_0's l1: 1.78333e+06
[12]	valid_0's l1: 1.75664e+06
[13]	valid_0's l1: 1.72714e+06
[14]	valid_0's l1: 1.72713e+06
[15]	valid_0's l1: 1.70508e+06
[16]	valid_0's l1: 1.68751e+06
[17]	valid_0's l1: 1.67159e+06
[18]	valid_0's l1: 1.66508e+06
[19]	valid_0's l1: 1.66682e+06
[20]	valid_0's l1: 1.65486e+06
[21]	valid_0's l1: 1.65807e+06
[22]	valid_0's l1: 1.65513e+06
[23]	valid_0's l1: 1.65293e+06
[24]	valid_0's l1: 1.65676e+06
[25]	valid_0's l1: 1.6567e+06
[26]	valid_0's l1: 1.65246e+06
[27]	valid_0's l1: 1.65489e+06
[28]	valid_0's l1: 1.6542e+06
[29]	valid_0's l1: 1.65756e+06
[30]	valid_0's l1: 1.64798e+06
[31]	valid_0's l1: 1.64311e+06
[32]	valid_0's l1: 1.64597e+06
[33]	valid_0's l1: 1.6487e+06
[34]	valid_0's l1: 1.65293e+06
[35]	valid_0's l1: 1.65345e+06
[36]	valid_0's l1: 1.65514e+06
[37]	valid_0's l1: 1.65351e+06
[38]	valid_0's l1: 1.65272e+06
[39]	valid_0's l1: 1.65673e+06
[40]	valid_0's l1: 1.65663e+06
[41]	valid_0's l1: 1.65784e+06
[42]	valid_0's l1: 1.65672e+06
[43]	valid_0's l1: 1.65752e+06
[44]	valid_0's l1: 1.65753e+06
[45]	valid_0's l1: 1.65528e+06
[46]	valid_0's l1: 1.66035e+06
[47]	valid_0's l1: 1.66167e+06
[48]	valid_0's l1: 1.66245e+06
[49]	valid_0's l1: 1.66084e+06
[50]	valid_0's l1: 1.66428e+06
[51]	valid_0's l1: 1.66446e+06
[52]	valid_0's l1: 1.66727e+06
[53]	valid_0's l1: 1.67062e+06
[54]	valid_0's l1: 1.67354e+06
[55]	valid_0's l1: 1.67543e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67716e+06
[58]	valid_0's l1: 1.67859e+06
[59]	valid_0's l1: 1.68064e+06
[60]	valid_0's l1: 1.68223e+06
[61]	valid_0's l1: 1.68239e+06
Early stopping, best iteration is:
[31]	valid_0's l1: 1.64311e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.67303e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.15957e+06
[3]	valid_0's l1: 2.74986e+06
[4]	valid_0's l1: 2.45151e+06
[5]	valid_0's l1: 2.23013e+06
[6]	valid_0's l1: 2.15413e+06
[7]	valid_0's l1: 2.08852e+06
[8]	valid_0's l1: 1.97426e+06
[9]	valid_0's l1: 1.88784e+06
[10]	valid_0's l1: 1.82639e+06
[11]	valid_0's l1: 1.77641e+06
[12]	valid_0's l1: 1.7611e+06
[13]	valid_0's l1: 1.7281e+06
[14]	valid_0's l1: 1.71859e+06
[15]	valid_0's l1: 1.69797e+06
[16]	valid_0's l1: 1.68329e+06
[17]	valid_0's l1: 1.68038e+06
[18]	valid_0's l1: 1.66907e+06
[19]	valid_0's l1: 1.66621e+06
[20]	valid_0's l1: 1.66287e+06
[21]	valid_0's l1: 1.66018e+06
[22]	valid_0's l1: 1.66398e+06
[23]	valid_0's l1: 1.66027e+06
[24]	valid_0's l1: 1.66435e+06
[25]	valid_0's l1: 1.65992e+06
[26]	valid_0's l1: 1.66286e+06
[27]	valid_0's l1: 1.65973e+06
[28]	valid_0's l1: 1.65974e+06
[29]	valid_0's l1: 1.6571e+06
[30]	valid_0's l1: 1.65502e+06
[31]	valid_0's l1: 1.65876e+06
[32]	valid_0's l1: 1.66014e+06
[33]	valid_0's l1: 1.6561e+06
[34]	valid_0's l1: 1.65872e+06
[35]	valid_0's l1: 1.65888e+06
[36]	valid_0's l1: 1.65659e+06
[37]	valid_0's l1: 1.65984e+06
[38]	valid_0's l1: 1.65935e+06
[39]	valid_0's l1: 1.6611e+06
[40]	valid_0's l1: 1.66236e+06
[41]	valid_0's l1: 1.65998e+06
[42]	valid_0's l1: 1.66392e+06
[43]	valid_0's l1: 1.66179e+06
[44]	valid_0's l1: 1.66272e+06
[45]	valid_0's l1: 1.66274e+06
[46]	valid_0's l1: 1.66192e+06
[47]	valid_0's l1: 1.66486e+06
[48]	valid_0's l1: 1.66293e+06
[49]	valid_0's l1: 1.6636e+06
[50]	valid_0's l1: 1.66386e+06
[51]	valid_0's l1: 1.66824e+06
[52]	valid_0's l1: 1.66677e+06
[53]	valid_0's l1: 1.67165e+06
[54]	valid_0's l1: 1.67538e+06
[55]	valid_0's l1: 1.67742e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67701e+06
[58]	valid_0's l1: 1.67817e+06
[59]	valid_0's l1: 1.67647e+06
[60]	valid_0's l1: 1.67678e+06
Early stopping, best iteration is:
[30]	valid_0's l1: 1.65502e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.74198e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17925e+06
[3]	valid_0's l1: 2.75493e+06
[4]	valid_0's l1: 2.43331e+06
[5]	valid_0's l1: 2.21332e+06
[6]	valid_0's l1: 2.1413e+06
[7]	valid_0's l1: 2.09055e+06
[8]	valid_0's l1: 1.97663e+06
[9]	valid_0's l1: 1.88299e+06
[10]	valid_0's l1: 1.81844e+06
[11]	valid_0's l1: 1.76375e+06
[12]	valid_0's l1: 1.74997e+06
[13]	valid_0's l1: 1.71063e+06
[14]	valid_0's l1: 1.70095e+06
[15]	valid_0's l1: 1.68101e+06
[16]	valid_0's l1: 1.6596e+06
[17]	valid_0's l1: 1.65919e+06
[18]	valid_0's l1: 1.64736e+06
[19]	valid_0's l1: 1.64521e+06
[20]	valid_0's l1: 1.64499e+06
[21]	valid_0's l1: 1.63518e+06
[22]	valid_0's l1: 1.63929e+06
[23]	valid_0's l1: 1.64545e+06
[24]	valid_0's l1: 1.64718e+06
[25]	valid_0's l1: 1.64141e+06
[26]	valid_0's l1: 1.64456e+06
[27]	valid_0's l1: 1.64418e+06
[28]	valid_0's l1: 1.64485e+06
[29]	valid_0's l1: 1.65057e+06
[30]	valid_0's l1: 1.65105e+06
[31]	valid_0's l1: 1.65194e+06
[32]	valid_0's l1: 1.65609e+06
[33]	valid_0's l1: 1.65301e+06
[34]	valid_0's l1: 1.65495e+06
[35]	valid_0's l1: 1.65622e+06
[36]	valid_0's l1: 1.66002e+06
[37]	valid_0's l1: 1.66264e+06
[38]	valid_0's l1: 1.66355e+06
[39]	valid_0's l1: 1.66487e+06
[40]	valid_0's l1: 1.66699e+06
[41]	valid_0's l1: 1.66554e+06
[42]	valid_0's l1: 1.66476e+06
[43]	valid_0's l1: 1.66452e+06
[44]	valid_0's l1: 1.66608e+06
[45]	valid_0's l1: 1.66929e+06
[46]	valid_0's l1: 1.66908e+06
[47]	valid_0's l1: 1.66932e+06
[48]	valid_0's l1: 1.66901e+06
[49]	valid_0's l1: 1.66908e+06
[50]	valid_0's l1: 1.67006e+06
[51]	valid_0's l1: 1.66873e+06
Early stopping, best iteration is:
[21]	valid_0's l1: 1.63518e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7172e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17345e+06
[3]	valid_0's l1: 2.77403e+06
[4]	valid_0's l1: 2.47886e+06
[5]	valid_0's l1: 2.26288e+06
[6]	valid_0's l1: 2.19668e+06
[7]	valid_0's l1: 2.14756e+06
[8]	valid_0's l1: 2.00628e+06
[9]	valid_0's l1: 1.90309e+06
[10]	valid_0's l1: 1.84191e+06
[11]	valid_0's l1: 1.78333e+06
[12]	valid_0's l1: 1.75664e+06
[13]	valid_0's l1: 1.72714e+06
[14]	valid_0's l1: 1.72713e+06
[15]	valid_0's l1: 1.70508e+06
[16]	valid_0's l1: 1.68751e+06
[17]	valid_0's l1: 1.67159e+06
[18]	valid_0's l1: 1.66508e+06
[19]	valid_0's l1: 1.66682e+06
[20]	valid_0's l1: 1.65486e+06
[21]	valid_0's l1: 1.65807e+06
[22]	valid_0's l1: 1.65513e+06
[23]	valid_0's l1: 1.65293e+06
[24]	valid_0's l1: 1.65676e+06
[25]	valid_0's l1: 1.6567e+06
[26]	valid_0's l1: 1.65246e+06
[27]	valid_0's l1: 1.65489e+06
[28]	valid_0's l1: 1.6542e+06
[29]	valid_0's l1: 1.65756e+06
[30]	valid_0's l1: 1.64798e+06
[31]	valid_0's l1: 1.64311e+06
[32]	valid_0's l1: 1.64597e+06
[33]	valid_0's l1: 1.6487e+06
[34]	valid_0's l1: 1.65293e+06
[35]	valid_0's l1: 1.65345e+06
[36]	valid_0's l1: 1.65514e+06
[37]	valid_0's l1: 1.65351e+06
[38]	valid_0's l1: 1.65272e+06
[39]	valid_0's l1: 1.65673e+06
[40]	valid_0's l1: 1.65663e+06
[41]	valid_0's l1: 1.65784e+06
[42]	valid_0's l1: 1.65672e+06
[43]	valid_0's l1: 1.65752e+06
[44]	valid_0's l1: 1.65753e+06
[45]	valid_0's l1: 1.65528e+06
[46]	valid_0's l1: 1.66035e+06
[47]	valid_0's l1: 1.66167e+06
[48]	valid_0's l1: 1.66245e+06
[49]	valid_0's l1: 1.66084e+06
[50]	valid_0's l1: 1.66428e+06
[51]	valid_0's l1: 1.66446e+06
[52]	valid_0's l1: 1.66727e+06
[53]	valid_0's l1: 1.67062e+06
[54]	valid_0's l1: 1.67354e+06
[55]	valid_0's l1: 1.67543e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67716e+06
[58]	valid_0's l1: 1.67859e+06
[59]	valid_0's l1: 1.68064e+06
[60]	valid_0's l1: 1.68223e+06
[61]	valid_0's l1: 1.68239e+06
Early stopping, best iteration is:
[31]	valid_0's l1: 1.64311e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.67303e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.15957e+06
[3]	valid_0's l1: 2.74986e+06
[4]	valid_0's l1: 2.45151e+06
[5]	valid_0's l1: 2.23013e+06
[6]	valid_0's l1: 2.15413e+06
[7]	valid_0's l1: 2.08852e+06
[8]	valid_0's l1: 1.97426e+06
[9]	valid_0's l1: 1.88784e+06
[10]	valid_0's l1: 1.82639e+06
[11]	valid_0's l1: 1.77641e+06
[12]	valid_0's l1: 1.7611e+06
[13]	valid_0's l1: 1.7281e+06
[14]	valid_0's l1: 1.71859e+06
[15]	valid_0's l1: 1.69797e+06
[16]	valid_0's l1: 1.68329e+06
[17]	valid_0's l1: 1.68038e+06
[18]	valid_0's l1: 1.66907e+06
[19]	valid_0's l1: 1.66621e+06
[20]	valid_0's l1: 1.66287e+06
[21]	valid_0's l1: 1.66018e+06
[22]	valid_0's l1: 1.66398e+06
[23]	valid_0's l1: 1.66027e+06
[24]	valid_0's l1: 1.66435e+06
[25]	valid_0's l1: 1.65992e+06
[26]	valid_0's l1: 1.66286e+06
[27]	valid_0's l1: 1.65973e+06
[28]	valid_0's l1: 1.65974e+06
[29]	valid_0's l1: 1.6571e+06
[30]	valid_0's l1: 1.65502e+06
[31]	valid_0's l1: 1.65876e+06
[32]	valid_0's l1: 1.66014e+06
[33]	valid_0's l1: 1.6561e+06
[34]	valid_0's l1: 1.65872e+06
[35]	valid_0's l1: 1.65888e+06
[36]	valid_0's l1: 1.65659e+06
[37]	valid_0's l1: 1.65984e+06
[38]	valid_0's l1: 1.65935e+06
[39]	valid_0's l1: 1.6611e+06
[40]	valid_0's l1: 1.66236e+06
[41]	valid_0's l1: 1.65998e+06
[42]	valid_0's l1: 1.66392e+06
[43]	valid_0's l1: 1.66179e+06
[44]	valid_0's l1: 1.66272e+06
[45]	valid_0's l1: 1.66274e+06
[46]	valid_0's l1: 1.66192e+06
[47]	valid_0's l1: 1.66486e+06
[48]	valid_0's l1: 1.66293e+06
[49]	valid_0's l1: 1.6636e+06
[50]	valid_0's l1: 1.66386e+06
[51]	valid_0's l1: 1.66824e+06
[52]	valid_0's l1: 1.66677e+06
[53]	valid_0's l1: 1.67165e+06
[54]	valid_0's l1: 1.67538e+06
[55]	valid_0's l1: 1.67742e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67701e+06
[58]	valid_0's l1: 1.67817e+06
[59]	valid_0's l1: 1.67647e+06
[60]	valid_0's l1: 1.67678e+06
Early stopping, best iteration is:
[30]	valid_0's l1: 1.65502e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.74198e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17925e+06
[3]	valid_0's l1: 2.75493e+06
[4]	valid_0's l1: 2.43331e+06
[5]	valid_0's l1: 2.21332e+06
[6]	valid_0's l1: 2.1413e+06
[7]	valid_0's l1: 2.09055e+06
[8]	valid_0's l1: 1.97663e+06
[9]	valid_0's l1: 1.88299e+06
[10]	valid_0's l1: 1.81844e+06
[11]	valid_0's l1: 1.76375e+06
[12]	valid_0's l1: 1.74997e+06
[13]	valid_0's l1: 1.71063e+06
[14]	valid_0's l1: 1.70095e+06
[15]	valid_0's l1: 1.68101e+06
[16]	valid_0's l1: 1.6596e+06
[17]	valid_0's l1: 1.65919e+06
[18]	valid_0's l1: 1.64736e+06
[19]	valid_0's l1: 1.64521e+06
[20]	valid_0's l1: 1.64499e+06
[21]	valid_0's l1: 1.63518e+06
[22]	valid_0's l1: 1.63929e+06
[23]	valid_0's l1: 1.64545e+06
[24]	valid_0's l1: 1.64718e+06
[25]	valid_0's l1: 1.64141e+06
[26]	valid_0's l1: 1.64456e+06
[27]	valid_0's l1: 1.64418e+06
[28]	valid_0's l1: 1.64485e+06
[29]	valid_0's l1: 1.65057e+06
[30]	valid_0's l1: 1.65105e+06
[31]	valid_0's l1: 1.65194e+06
[32]	valid_0's l1: 1.65609e+06
[33]	valid_0's l1: 1.65301e+06
[34]	valid_0's l1: 1.65495e+06
[35]	valid_0's l1: 1.65622e+06
[36]	valid_0's l1: 1.66002e+06
[37]	valid_0's l1: 1.66264e+06
[38]	valid_0's l1: 1.66355e+06
[39]	valid_0's l1: 1.66487e+06
[40]	valid_0's l1: 1.66699e+06
[41]	valid_0's l1: 1.66554e+06
[42]	valid_0's l1: 1.66476e+06
[43]	valid_0's l1: 1.66452e+06
[44]	valid_0's l1: 1.66608e+06
[45]	valid_0's l1: 1.66929e+06
[46]	valid_0's l1: 1.66908e+06
[47]	valid_0's l1: 1.66932e+06
[48]	valid_0's l1: 1.66901e+06
[49]	valid_0's l1: 1.66908e+06
[50]	valid_0's l1: 1.67006e+06
[51]	valid_0's l1: 1.66873e+06
Early stopping, best iteration is:
[21]	valid_0's l1: 1.63518e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7172e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17345e+06
[3]	valid_0's l1: 2.77403e+06
[4]	valid_0's l1: 2.47886e+06
[5]	valid_0's l1: 2.26288e+06
[6]	valid_0's l1: 2.19668e+06
[7]	valid_0's l1: 2.14756e+06
[8]	valid_0's l1: 2.00628e+06
[9]	valid_0's l1: 1.90309e+06
[10]	valid_0's l1: 1.84191e+06
[11]	valid_0's l1: 1.78333e+06
[12]	valid_0's l1: 1.75664e+06
[13]	valid_0's l1: 1.72714e+06
[14]	valid_0's l1: 1.72713e+06
[15]	valid_0's l1: 1.70508e+06
[16]	valid_0's l1: 1.68751e+06
[17]	valid_0's l1: 1.67159e+06
[18]	valid_0's l1: 1.66508e+06
[19]	valid_0's l1: 1.66682e+06
[20]	valid_0's l1: 1.65486e+06
[21]	valid_0's l1: 1.65807e+06
[22]	valid_0's l1: 1.65513e+06
[23]	valid_0's l1: 1.65293e+06
[24]	valid_0's l1: 1.65676e+06
[25]	valid_0's l1: 1.6567e+06
[26]	valid_0's l1: 1.65246e+06
[27]	valid_0's l1: 1.65489e+06
[28]	valid_0's l1: 1.6542e+06
[29]	valid_0's l1: 1.65756e+06
[30]	valid_0's l1: 1.64798e+06
[31]	valid_0's l1: 1.64311e+06
[32]	valid_0's l1: 1.64597e+06
[33]	valid_0's l1: 1.6487e+06
[34]	valid_0's l1: 1.65293e+06
[35]	valid_0's l1: 1.65345e+06
[36]	valid_0's l1: 1.65514e+06
[37]	valid_0's l1: 1.65351e+06
[38]	valid_0's l1: 1.65272e+06
[39]	valid_0's l1: 1.65673e+06
[40]	valid_0's l1: 1.65663e+06
[41]	valid_0's l1: 1.65784e+06
[42]	valid_0's l1: 1.65672e+06
[43]	valid_0's l1: 1.65752e+06
[44]	valid_0's l1: 1.65753e+06
[45]	valid_0's l1: 1.65528e+06
[46]	valid_0's l1: 1.66035e+06
[47]	valid_0's l1: 1.66167e+06
[48]	valid_0's l1: 1.66245e+06
[49]	valid_0's l1: 1.66084e+06
[50]	valid_0's l1: 1.66428e+06
[51]	valid_0's l1: 1.66446e+06
[52]	valid_0's l1: 1.66727e+06
[53]	valid_0's l1: 1.67062e+06
[54]	valid_0's l1: 1.67354e+06
[55]	valid_0's l1: 1.67543e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67716e+06
[58]	valid_0's l1: 1.67859e+06
[59]	valid_0's l1: 1.68064e+06
[60]	valid_0's l1: 1.68223e+06
[61]	valid_0's l1: 1.68239e+06
Early stopping, best iteration is:
[31]	valid_0's l1: 1.64311e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.67303e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.15957e+06
[3]	valid_0's l1: 2.74986e+06
[4]	valid_0's l1: 2.45151e+06
[5]	valid_0's l1: 2.23013e+06
[6]	valid_0's l1: 2.15413e+06
[7]	valid_0's l1: 2.08852e+06
[8]	valid_0's l1: 1.97426e+06
[9]	valid_0's l1: 1.88784e+06
[10]	valid_0's l1: 1.82639e+06
[11]	valid_0's l1: 1.77641e+06
[12]	valid_0's l1: 1.7611e+06
[13]	valid_0's l1: 1.7281e+06
[14]	valid_0's l1: 1.71859e+06
[15]	valid_0's l1: 1.69797e+06
[16]	valid_0's l1: 1.68329e+06
[17]	valid_0's l1: 1.68038e+06
[18]	valid_0's l1: 1.66907e+06
[19]	valid_0's l1: 1.66621e+06
[20]	valid_0's l1: 1.66287e+06
[21]	valid_0's l1: 1.66018e+06
[22]	valid_0's l1: 1.66398e+06
[23]	valid_0's l1: 1.66027e+06
[24]	valid_0's l1: 1.66435e+06
[25]	valid_0's l1: 1.65992e+06
[26]	valid_0's l1: 1.66286e+06
[27]	valid_0's l1: 1.65973e+06
[28]	valid_0's l1: 1.65974e+06
[29]	valid_0's l1: 1.6571e+06
[30]	valid_0's l1: 1.65502e+06
[31]	valid_0's l1: 1.65876e+06
[32]	valid_0's l1: 1.66014e+06
[33]	valid_0's l1: 1.6561e+06
[34]	valid_0's l1: 1.65872e+06
[35]	valid_0's l1: 1.65888e+06
[36]	valid_0's l1: 1.65659e+06
[37]	valid_0's l1: 1.65984e+06
[38]	valid_0's l1: 1.65935e+06
[39]	valid_0's l1: 1.6611e+06
[40]	valid_0's l1: 1.66236e+06
[41]	valid_0's l1: 1.65998e+06
[42]	valid_0's l1: 1.66392e+06
[43]	valid_0's l1: 1.66179e+06
[44]	valid_0's l1: 1.66272e+06
[45]	valid_0's l1: 1.66274e+06
[46]	valid_0's l1: 1.66192e+06
[47]	valid_0's l1: 1.66486e+06
[48]	valid_0's l1: 1.66293e+06
[49]	valid_0's l1: 1.6636e+06
[50]	valid_0's l1: 1.66386e+06
[51]	valid_0's l1: 1.66824e+06
[52]	valid_0's l1: 1.66677e+06
[53]	valid_0's l1: 1.67165e+06
[54]	valid_0's l1: 1.67538e+06
[55]	valid_0's l1: 1.67742e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67701e+06
[58]	valid_0's l1: 1.67817e+06
[59]	valid_0's l1: 1.67647e+06
[60]	valid_0's l1: 1.67678e+06
Early stopping, best iteration is:
[30]	valid_0's l1: 1.65502e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.74198e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17925e+06
[3]	valid_0's l1: 2.75493e+06
[4]	valid_0's l1: 2.43331e+06
[5]	valid_0's l1: 2.21332e+06
[6]	valid_0's l1: 2.1413e+06
[7]	valid_0's l1: 2.09055e+06
[8]	valid_0's l1: 1.97663e+06
[9]	valid_0's l1: 1.88299e+06
[10]	valid_0's l1: 1.81844e+06
[11]	valid_0's l1: 1.76375e+06
[12]	valid_0's l1: 1.74997e+06
[13]	valid_0's l1: 1.71063e+06
[14]	valid_0's l1: 1.70095e+06
[15]	valid_0's l1: 1.68101e+06
[16]	valid_0's l1: 1.6596e+06
[17]	valid_0's l1: 1.65919e+06
[18]	valid_0's l1: 1.64736e+06
[19]	valid_0's l1: 1.64521e+06
[20]	valid_0's l1: 1.64499e+06
[21]	valid_0's l1: 1.63518e+06
[22]	valid_0's l1: 1.63929e+06
[23]	valid_0's l1: 1.64545e+06
[24]	valid_0's l1: 1.64718e+06
[25]	valid_0's l1: 1.64141e+06
[26]	valid_0's l1: 1.64456e+06
[27]	valid_0's l1: 1.64418e+06
[28]	valid_0's l1: 1.64485e+06
[29]	valid_0's l1: 1.65057e+06
[30]	valid_0's l1: 1.65105e+06
[31]	valid_0's l1: 1.65194e+06
[32]	valid_0's l1: 1.65609e+06
[33]	valid_0's l1: 1.65301e+06
[34]	valid_0's l1: 1.65495e+06
[35]	valid_0's l1: 1.65622e+06
[36]	valid_0's l1: 1.66002e+06
[37]	valid_0's l1: 1.66264e+06
[38]	valid_0's l1: 1.66355e+06
[39]	valid_0's l1: 1.66487e+06
[40]	valid_0's l1: 1.66699e+06
[41]	valid_0's l1: 1.66554e+06
[42]	valid_0's l1: 1.66476e+06
[43]	valid_0's l1: 1.66452e+06
[44]	valid_0's l1: 1.66608e+06
[45]	valid_0's l1: 1.66929e+06
[46]	valid_0's l1: 1.66908e+06
[47]	valid_0's l1: 1.66932e+06
[48]	valid_0's l1: 1.66901e+06
[49]	valid_0's l1: 1.66908e+06
[50]	valid_0's l1: 1.67006e+06
[51]	valid_0's l1: 1.66873e+06
Early stopping, best iteration is:
[21]	valid_0's l1: 1.63518e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.7172e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17345e+06
[3]	valid_0's l1: 2.77403e+06
[4]	valid_0's l1: 2.47886e+06
[5]	valid_0's l1: 2.26288e+06
[6]	valid_0's l1: 2.19668e+06
[7]	valid_0's l1: 2.14756e+06
[8]	valid_0's l1: 2.00628e+06
[9]	valid_0's l1: 1.90309e+06
[10]	valid_0's l1: 1.84191e+06
[11]	valid_0's l1: 1.78333e+06
[12]	valid_0's l1: 1.75664e+06
[13]	valid_0's l1: 1.72714e+06
[14]	valid_0's l1: 1.72713e+06
[15]	valid_0's l1: 1.70508e+06
[16]	valid_0's l1: 1.68751e+06
[17]	valid_0's l1: 1.67159e+06
[18]	valid_0's l1: 1.66508e+06
[19]	valid_0's l1: 1.66682e+06
[20]	valid_0's l1: 1.65486e+06
[21]	valid_0's l1: 1.65807e+06
[22]	valid_0's l1: 1.65513e+06
[23]	valid_0's l1: 1.65293e+06
[24]	valid_0's l1: 1.65676e+06
[25]	valid_0's l1: 1.6567e+06
[26]	valid_0's l1: 1.65246e+06
[27]	valid_0's l1: 1.65489e+06
[28]	valid_0's l1: 1.6542e+06
[29]	valid_0's l1: 1.65756e+06
[30]	valid_0's l1: 1.64798e+06
[31]	valid_0's l1: 1.64311e+06
[32]	valid_0's l1: 1.64597e+06
[33]	valid_0's l1: 1.6487e+06
[34]	valid_0's l1: 1.65293e+06
[35]	valid_0's l1: 1.65345e+06
[36]	valid_0's l1: 1.65514e+06
[37]	valid_0's l1: 1.65351e+06
[38]	valid_0's l1: 1.65272e+06
[39]	valid_0's l1: 1.65673e+06
[40]	valid_0's l1: 1.65663e+06
[41]	valid_0's l1: 1.65784e+06
[42]	valid_0's l1: 1.65672e+06
[43]	valid_0's l1: 1.65752e+06
[44]	valid_0's l1: 1.65753e+06
[45]	valid_0's l1: 1.65528e+06
[46]	valid_0's l1: 1.66035e+06
[47]	valid_0's l1: 1.66167e+06
[48]	valid_0's l1: 1.66245e+06
[49]	valid_0's l1: 1.66084e+06
[50]	valid_0's l1: 1.66428e+06
[51]	valid_0's l1: 1.66446e+06
[52]	valid_0's l1: 1.66727e+06
[53]	valid_0's l1: 1.67062e+06
[54]	valid_0's l1: 1.67354e+06
[55]	valid_0's l1: 1.67543e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67716e+06
[58]	valid_0's l1: 1.67859e+06
[59]	valid_0's l1: 1.68064e+06
[60]	valid_0's l1: 1.68223e+06
[61]	valid_0's l1: 1.68239e+06
Early stopping, best iteration is:
[31]	valid_0's l1: 1.64311e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.67303e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.15957e+06
[3]	valid_0's l1: 2.74986e+06
[4]	valid_0's l1: 2.45151e+06
[5]	valid_0's l1: 2.23013e+06
[6]	valid_0's l1: 2.15413e+06
[7]	valid_0's l1: 2.08852e+06
[8]	valid_0's l1: 1.97426e+06
[9]	valid_0's l1: 1.88784e+06
[10]	valid_0's l1: 1.82639e+06
[11]	valid_0's l1: 1.77641e+06
[12]	valid_0's l1: 1.7611e+06
[13]	valid_0's l1: 1.7281e+06
[14]	valid_0's l1: 1.71859e+06
[15]	valid_0's l1: 1.69797e+06
[16]	valid_0's l1: 1.68329e+06
[17]	valid_0's l1: 1.68038e+06
[18]	valid_0's l1: 1.66907e+06
[19]	valid_0's l1: 1.66621e+06
[20]	valid_0's l1: 1.66287e+06
[21]	valid_0's l1: 1.66018e+06
[22]	valid_0's l1: 1.66398e+06
[23]	valid_0's l1: 1.66027e+06
[24]	valid_0's l1: 1.66435e+06
[25]	valid_0's l1: 1.65992e+06
[26]	valid_0's l1: 1.66286e+06
[27]	valid_0's l1: 1.65973e+06
[28]	valid_0's l1: 1.65974e+06
[29]	valid_0's l1: 1.6571e+06
[30]	valid_0's l1: 1.65502e+06
[31]	valid_0's l1: 1.65876e+06
[32]	valid_0's l1: 1.66014e+06
[33]	valid_0's l1: 1.6561e+06
[34]	valid_0's l1: 1.65872e+06
[35]	valid_0's l1: 1.65888e+06
[36]	valid_0's l1: 1.65659e+06
[37]	valid_0's l1: 1.65984e+06
[38]	valid_0's l1: 1.65935e+06
[39]	valid_0's l1: 1.6611e+06
[40]	valid_0's l1: 1.66236e+06
[41]	valid_0's l1: 1.65998e+06
[42]	valid_0's l1: 1.66392e+06
[43]	valid_0's l1: 1.66179e+06
[44]	valid_0's l1: 1.66272e+06
[45]	valid_0's l1: 1.66274e+06
[46]	valid_0's l1: 1.66192e+06
[47]	valid_0's l1: 1.66486e+06
[48]	valid_0's l1: 1.66293e+06
[49]	valid_0's l1: 1.6636e+06
[50]	valid_0's l1: 1.66386e+06
[51]	valid_0's l1: 1.66824e+06
[52]	valid_0's l1: 1.66677e+06
[53]	valid_0's l1: 1.67165e+06
[54]	valid_0's l1: 1.67538e+06
[55]	valid_0's l1: 1.67742e+06
[56]	valid_0's l1: 1.67659e+06
[57]	valid_0's l1: 1.67701e+06
[58]	valid_0's l1: 1.67817e+06
[59]	valid_0's l1: 1.67647e+06
[60]	valid_0's l1: 1.67678e+06
Early stopping, best iteration is:
[30]	valid_0's l1: 1.65502e+06
[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.74198e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.17925e+06
[3]	valid_0's l1: 2.75493e+06
[4]	valid_0's l1: 2.43331e+06
[5]	valid_0's l1: 2.21332e+06
[6]	valid_0's l1: 2.1413e+06
[7]	valid_0's l1: 2.09055e+06
[8]	valid_0's l1: 1.97663e+06
[9]	valid_0's l1: 1.88299e+06
[10]	valid_0's l1: 1.81844e+06
[11]	valid_0's l1: 1.76375e+06
[12]	valid_0's l1: 1.74997e+06
[13]	valid_0's l1: 1.71063e+06
[14]	valid_0's l1: 1.70095e+06
[15]	valid_0's l1: 1.68101e+06
[16]	valid_0's l1: 1.6596e+06
[17]	valid_0's l1: 1.65919e+06
[18]	valid_0's l1: 1.64736e+06
[19]	valid_0's l1: 1.64521e+06
[20]	valid_0's l1: 1.64499e+06
[21]	valid_0's l1: 1.63518e+06
[22]	valid_0's l1: 1.63929e+06
[23]	valid_0's l1: 1.64545e+06
[24]	valid_0's l1: 1.64718e+06
[25]	valid_0's l1: 1.64141e+06
[26]	valid_0's l1: 1.64456e+06
[27]	valid_0's l1: 1.64418e+06
[28]	valid_0's l1: 1.64485e+06
[29]	valid_0's l1: 1.65057e+06
[30]	valid_0's l1: 1.65105e+06
[31]	valid_0's l1: 1.65194e+06
[32]	valid_0's l1: 1.65609e+06
[33]	valid_0's l1: 1.65301e+06
[34]	valid_0's l1: 1.65495e+06
[35]	valid_0's l1: 1.65622e+06
[36]	valid_0's l1: 1.66002e+06
[37]	valid_0's l1: 1.66264e+06
[38]	valid_0's l1: 1.66355e+06
[39]	valid_0's l1: 1.66487e+06
[40]	valid_0's l1: 1.66699e+06
[41]	valid_0's l1: 1.66554e+06
[42]	valid_0's l1: 1.66476e+06
[43]	valid_0's l1: 1.66452e+06
[44]	valid_0's l1: 1.66608e+06
[45]	valid_0's l1: 1.66929e+06
[46]	valid_0's l1: 1.66908e+06
[47]	valid_0's l1: 1.66932e+06
[48]	valid_0's l1: 1.66901e+06
[49]	valid_0's l1: 1.66908e+06
[50]	valid_0's l1: 1.67006e+06
[51]	valid_0's l1: 1.66873e+06
Early stopping, best iteration is:
[21]	valid_0's l1: 1.63518e+06

[Parallel(n_jobs=1)]: Done 108 out of 108 | elapsed:  2.6min finished
C:\Users\YAVUZ\anaconda3\lib\site-packages\sklearn\model_selection\_search.py:847: FutureWarning:

The parameter 'iid' is deprecated in 0.22 and will be removed in 0.24.

[LightGBM] [Warning] feature_fraction is set=0.8, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.8
[LightGBM] [Warning] bagging_fraction is set=0.8, subsample=1.0 will be ignored. Current value: bagging_fraction=0.8
[1]	valid_0's l1: 3.86831e+06
Training until validation scores don't improve for 30 rounds
[2]	valid_0's l1: 3.56444e+06
[3]	valid_0's l1: 3.29847e+06
[4]	valid_0's l1: 3.0627e+06
[5]	valid_0's l1: 2.85804e+06
[6]	valid_0's l1: 2.75834e+06
[7]	valid_0's l1: 2.6784e+06
[8]	valid_0's l1: 2.52683e+06
[9]	valid_0's l1: 2.3987e+06
[10]	valid_0's l1: 2.28371e+06
[11]	valid_0's l1: 2.18641e+06
[12]	valid_0's l1: 2.13955e+06
[13]	valid_0's l1: 2.06087e+06
[14]	valid_0's l1: 2.03278e+06
[15]	valid_0's l1: 1.96801e+06
[16]	valid_0's l1: 1.90775e+06
[17]	valid_0's l1: 1.86176e+06
[18]	valid_0's l1: 1.82014e+06
[19]	valid_0's l1: 1.78398e+06
[20]	valid_0's l1: 1.75302e+06
[21]	valid_0's l1: 1.72988e+06
[22]	valid_0's l1: 1.7051e+06
[23]	valid_0's l1: 1.68279e+06
[24]	valid_0's l1: 1.66601e+06
[25]	valid_0's l1: 1.65001e+06
[26]	valid_0's l1: 1.6369e+06
[27]	valid_0's l1: 1.62504e+06
[28]	valid_0's l1: 1.61374e+06
[29]	valid_0's l1: 1.60745e+06
[30]	valid_0's l1: 1.60007e+06
[31]	valid_0's l1: 1.59604e+06
[32]	valid_0's l1: 1.58828e+06
[33]	valid_0's l1: 1.58689e+06
[34]	valid_0's l1: 1.58121e+06
[35]	valid_0's l1: 1.57792e+06
[36]	valid_0's l1: 1.57232e+06
[37]	valid_0's l1: 1.57041e+06
[38]	valid_0's l1: 1.56866e+06
[39]	valid_0's l1: 1.56406e+06
[40]	valid_0's l1: 1.56267e+06
[41]	valid_0's l1: 1.56254e+06
[42]	valid_0's l1: 1.5593e+06
[43]	valid_0's l1: 1.55895e+06
[44]	valid_0's l1: 1.55912e+06
[45]	valid_0's l1: 1.55571e+06
[46]	valid_0's l1: 1.55615e+06
[47]	valid_0's l1: 1.55678e+06
[48]	valid_0's l1: 1.5567e+06
[49]	valid_0's l1: 1.55792e+06
[50]	valid_0's l1: 1.55928e+06
[51]	valid_0's l1: 1.5584e+06
[52]	valid_0's l1: 1.55888e+06
[53]	valid_0's l1: 1.5584e+06
[54]	valid_0's l1: 1.55833e+06
[55]	valid_0's l1: 1.55763e+06
[56]	valid_0's l1: 1.55671e+06
[57]	valid_0's l1: 1.55731e+06
[58]	valid_0's l1: 1.55619e+06
[59]	valid_0's l1: 1.55783e+06
[60]	valid_0's l1: 1.55753e+06
[61]	valid_0's l1: 1.55744e+06
[62]	valid_0's l1: 1.55883e+06
[63]	valid_0's l1: 1.55826e+06
[64]	valid_0's l1: 1.55896e+06
[65]	valid_0's l1: 1.56e+06
[66]	valid_0's l1: 1.55806e+06
[67]	valid_0's l1: 1.5583e+06
[68]	valid_0's l1: 1.55702e+06
[69]	valid_0's l1: 1.5565e+06
[70]	valid_0's l1: 1.55543e+06
[71]	valid_0's l1: 1.55591e+06
[72]	valid_0's l1: 1.55505e+06
[73]	valid_0's l1: 1.55459e+06
[74]	valid_0's l1: 1.55404e+06
[75]	valid_0's l1: 1.55336e+06
[76]	valid_0's l1: 1.55492e+06
[77]	valid_0's l1: 1.55441e+06
[78]	valid_0's l1: 1.55459e+06
[79]	valid_0's l1: 1.55399e+06
[80]	valid_0's l1: 1.55429e+06
[81]	valid_0's l1: 1.55362e+06
[82]	valid_0's l1: 1.55502e+06
[83]	valid_0's l1: 1.55553e+06
[84]	valid_0's l1: 1.55603e+06
[85]	valid_0's l1: 1.55555e+06
[86]	valid_0's l1: 1.55543e+06
[87]	valid_0's l1: 1.5554e+06
[88]	valid_0's l1: 1.556e+06
[89]	valid_0's l1: 1.55712e+06
[90]	valid_0's l1: 1.55612e+06
[91]	valid_0's l1: 1.55725e+06
[92]	valid_0's l1: 1.55686e+06
[93]	valid_0's l1: 1.55708e+06
[94]	valid_0's l1: 1.55698e+06
[95]	valid_0's l1: 1.55728e+06
[96]	valid_0's l1: 1.55628e+06
[97]	valid_0's l1: 1.55569e+06
[98]	valid_0's l1: 1.55562e+06
[99]	valid_0's l1: 1.5572e+06
[100]	valid_0's l1: 1.55752e+06
[101]	valid_0's l1: 1.55841e+06
[102]	valid_0's l1: 1.55924e+06
[103]	valid_0's l1: 1.55884e+06
[104]	valid_0's l1: 1.55992e+06
[105]	valid_0's l1: 1.55944e+06
Early stopping, best iteration is:
[75]	valid_0's l1: 1.55336e+06

GridSearchCV(cv=3,
             estimator=LGBMRegressor(bagging_fraction=0.8, feature_fraction=0.8,
                                     metric='mae', n_estimators=400,
                                     objective='regression', reg_lambda=0.9),
             iid=False, n_jobs=1,
             param_grid={'learning_rate': [0.1, 0.2], 'max_depth': [-1, 5, 6],
                         'n_estimators': [400, 800, 1200],
                         'num_leaves': [100, 200]},
             scoring='neg_mean_absolute_error', verbose=1)

gridSearchCV.best_params_, gridSearchCV.best_score_

({'learning_rate': 0.1,
  'max_depth': 6,
  'n_estimators': 400,
  'num_leaves': 100},
 -1713679.684827206)

gridSearchCV.cv_results_

{'mean_fit_time': array([2.3932662 , 3.23434997, 2.32777556, 3.09804734, 2.42152341,
        3.35436273, 0.8301127 , 0.83908947, 0.82147058, 0.8370947 ,
        0.82944957, 0.85437973, 0.95444759, 0.98835635, 1.03124221,
        0.89327717, 0.88097731, 0.88430134, 1.74333747, 2.38329228,
        1.69347024, 2.3965896 , 1.70510642, 2.34838597, 0.65624475,
        0.66256094, 0.66733479, 0.65458353, 0.65890511, 0.69181665,
        0.71176354, 0.71974134, 0.70611103, 0.7094357 , 0.70079255,
        0.71541897]),
 'std_fit_time': array([0.03092722, 0.26178615, 0.07828097, 0.20179714, 0.07059756,
        0.38703346, 0.0344082 , 0.09609417, 0.06700301, 0.06578449,
        0.05880252, 0.05896218, 0.09833752, 0.03546882, 0.04562376,
        0.06958622, 0.06108109, 0.03320003, 0.02973127, 0.02206609,
        0.04531787, 0.06538363, 0.04731745, 0.06895418, 0.02372722,
        0.02545794, 0.02495317, 0.02646674, 0.02315212, 0.01506651,
        0.03373644, 0.02631581, 0.02016165, 0.0195495 , 0.0236905 ,
        0.02578144]),
 'mean_score_time': array([0.08311057, 0.09108941, 0.09574254, 0.09109028, 0.07147598,
        0.08311025, 0.08577061, 0.08510621, 0.08211342, 0.08843048,
        0.09042374, 0.09075745, 0.08111684, 0.0591832 , 0.08344261,
        0.09175499, 0.08776522, 0.08842977, 0.08710027, 0.08843017,
        0.08543785, 0.09374984, 0.08709955, 0.0927527 , 0.0874327 ,
        0.0824465 , 0.09009202, 0.07346932, 0.08709939, 0.07513173,
        0.08710011, 0.080784  , 0.09208687, 0.08543841, 0.08543777,
        0.08277885]),
 'std_score_time': array([0.00588976, 0.00261774, 0.01058427, 0.00417813, 0.00600197,
        0.01879013, 0.0088085 , 0.01235916, 0.00248729, 0.001882  ,
        0.00235016, 0.0008143 , 0.01018219, 0.01180485, 0.00823781,
        0.00325641, 0.00282064, 0.0016947 , 0.00204936, 0.0024884 ,
        0.00094083, 0.0021545 , 0.0036714 , 0.00373164, 0.00046991,
        0.00477137, 0.00285933, 0.00702041, 0.00409853, 0.01093504,
        0.00621884, 0.01139998, 0.00169486, 0.00367217, 0.00401719,
        0.01139989]),
 'param_learning_rate': masked_array(data=[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
                    0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.2, 0.2, 0.2, 0.2,
                    0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
                    0.2, 0.2, 0.2],
              mask=[False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False],
        fill_value='?',
             dtype=object),
 'param_max_depth': masked_array(data=[-1, -1, -1, -1, -1, -1, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6,
                    6, 6, -1, -1, -1, -1, -1, -1, 5, 5, 5, 5, 5, 5, 6, 6,
                    6, 6, 6, 6],
              mask=[False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False],
        fill_value='?',
             dtype=object),
 'param_n_estimators': masked_array(data=[400, 400, 800, 800, 1200, 1200, 400, 400, 800, 800,
                    1200, 1200, 400, 400, 800, 800, 1200, 1200, 400, 400,
                    800, 800, 1200, 1200, 400, 400, 800, 800, 1200, 1200,
                    400, 400, 800, 800, 1200, 1200],
              mask=[False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False],
        fill_value='?',
             dtype=object),
 'param_num_leaves': masked_array(data=[100, 200, 100, 200, 100, 200, 100, 200, 100, 200, 100,
                    200, 100, 200, 100, 200, 100, 200, 100, 200, 100, 200,
                    100, 200, 100, 200, 100, 200, 100, 200, 100, 200, 100,
                    200, 100, 200],
              mask=[False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False, False, False, False, False,
                    False, False, False, False],
        fill_value='?',
             dtype=object),
 'params': [{'learning_rate': 0.1,
   'max_depth': -1,
   'n_estimators': 400,
   'num_leaves': 100},
  {'learning_rate': 0.1,
   'max_depth': -1,
   'n_estimators': 400,
   'num_leaves': 200},
  {'learning_rate': 0.1,
   'max_depth': -1,
   'n_estimators': 800,
   'num_leaves': 100},
  {'learning_rate': 0.1,
   'max_depth': -1,
   'n_estimators': 800,
   'num_leaves': 200},
  {'learning_rate': 0.1,
   'max_depth': -1,
   'n_estimators': 1200,
   'num_leaves': 100},
  {'learning_rate': 0.1,
   'max_depth': -1,
   'n_estimators': 1200,
   'num_leaves': 200},
  {'learning_rate': 0.1,
   'max_depth': 5,
   'n_estimators': 400,
   'num_leaves': 100},
  {'learning_rate': 0.1,
   'max_depth': 5,
   'n_estimators': 400,
   'num_leaves': 200},
  {'learning_rate': 0.1,
   'max_depth': 5,
   'n_estimators': 800,
   'num_leaves': 100},
  {'learning_rate': 0.1,
   'max_depth': 5,
   'n_estimators': 800,
   'num_leaves': 200},
  {'learning_rate': 0.1,
   'max_depth': 5,
   'n_estimators': 1200,
   'num_leaves': 100},
  {'learning_rate': 0.1,
   'max_depth': 5,
   'n_estimators': 1200,
   'num_leaves': 200},
  {'learning_rate': 0.1,
   'max_depth': 6,
   'n_estimators': 400,
   'num_leaves': 100},
  {'learning_rate': 0.1,
   'max_depth': 6,
   'n_estimators': 400,
   'num_leaves': 200},
  {'learning_rate': 0.1,
   'max_depth': 6,
   'n_estimators': 800,
   'num_leaves': 100},
  {'learning_rate': 0.1,
   'max_depth': 6,
   'n_estimators': 800,
   'num_leaves': 200},
  {'learning_rate': 0.1,
   'max_depth': 6,
   'n_estimators': 1200,
   'num_leaves': 100},
  {'learning_rate': 0.1,
   'max_depth': 6,
   'n_estimators': 1200,
   'num_leaves': 200},
  {'learning_rate': 0.2,
   'max_depth': -1,
   'n_estimators': 400,
   'num_leaves': 100},
  {'learning_rate': 0.2,
   'max_depth': -1,
   'n_estimators': 400,
   'num_leaves': 200},
  {'learning_rate': 0.2,
   'max_depth': -1,
   'n_estimators': 800,
   'num_leaves': 100},
  {'learning_rate': 0.2,
   'max_depth': -1,
   'n_estimators': 800,
   'num_leaves': 200},
  {'learning_rate': 0.2,
   'max_depth': -1,
   'n_estimators': 1200,
   'num_leaves': 100},
  {'learning_rate': 0.2,
   'max_depth': -1,
   'n_estimators': 1200,
   'num_leaves': 200},
  {'learning_rate': 0.2,
   'max_depth': 5,
   'n_estimators': 400,
   'num_leaves': 100},
  {'learning_rate': 0.2,
   'max_depth': 5,
   'n_estimators': 400,
   'num_leaves': 200},
  {'learning_rate': 0.2,
   'max_depth': 5,
   'n_estimators': 800,
   'num_leaves': 100},
  {'learning_rate': 0.2,
   'max_depth': 5,
   'n_estimators': 800,
   'num_leaves': 200},
  {'learning_rate': 0.2,
   'max_depth': 5,
   'n_estimators': 1200,
   'num_leaves': 100},
  {'learning_rate': 0.2,
   'max_depth': 5,
   'n_estimators': 1200,
   'num_leaves': 200},
  {'learning_rate': 0.2,
   'max_depth': 6,
   'n_estimators': 400,
   'num_leaves': 100},
  {'learning_rate': 0.2,
   'max_depth': 6,
   'n_estimators': 400,
   'num_leaves': 200},
  {'learning_rate': 0.2,
   'max_depth': 6,
   'n_estimators': 800,
   'num_leaves': 100},
  {'learning_rate': 0.2,
   'max_depth': 6,
   'n_estimators': 800,
   'num_leaves': 200},
  {'learning_rate': 0.2,
   'max_depth': 6,
   'n_estimators': 1200,
   'num_leaves': 100},
  {'learning_rate': 0.2,
   'max_depth': 6,
   'n_estimators': 1200,
   'num_leaves': 200}],
 'split0_test_score': array([-1708596.67757451, -1739473.27619857, -1708596.67757451,
        -1739473.27619857, -1708596.67757451, -1739473.27619857,
        -1703987.76040836, -1703987.76040836, -1703987.76040836,
        -1703987.76040836, -1703987.76040836, -1703987.76040836,
        -1700057.52596791, -1700057.52596791, -1700057.52596791,
        -1700057.52596791, -1700057.52596791, -1700057.52596791,
        -1814733.17601571, -1827893.6066538 , -1814733.17601571,
        -1827893.6066538 , -1814733.17601571, -1827893.6066538 ,
        -1740442.47062728, -1740442.47062728, -1740442.47062728,
        -1740442.47062728, -1740442.47062728, -1740442.47062728,
        -1739532.69179785, -1739532.69179785, -1739532.69179785,
        -1739532.69179785, -1739532.69179785, -1739532.69179785]),
 'split1_test_score': array([-1790858.56377364, -1780182.58900775, -1790858.56377364,
        -1780182.58900775, -1790858.56377364, -1780182.58900775,
        -1751622.93357624, -1751622.93357624, -1751622.93357624,
        -1751622.93357624, -1751622.93357624, -1751622.93357624,
        -1760564.16450841, -1760564.16450841, -1760564.16450841,
        -1760564.16450841, -1760564.16450841, -1760564.16450841,
        -1890928.97641883, -1894299.4831432 , -1890928.97641883,
        -1894299.4831432 , -1890928.97641883, -1894299.4831432 ,
        -1824776.86889778, -1824776.86889778, -1824776.86889778,
        -1824776.86889778, -1824776.86889778, -1824776.86889778,
        -1825484.92770088, -1825484.92770088, -1825484.92770088,
        -1825484.92770088, -1825484.92770088, -1825484.92770088]),
 'split2_test_score': array([-1690056.3933445 , -1697198.90649058, -1690056.3933445 ,
        -1697198.90649058, -1690056.3933445 , -1697198.90649058,
        -1703008.2654063 , -1703008.2654063 , -1703008.2654063 ,
        -1703008.2654063 , -1703008.2654063 , -1703008.2654063 ,
        -1680417.3640053 , -1680417.3640053 , -1680417.3640053 ,
        -1680417.3640053 , -1680417.3640053 , -1680417.3640053 ,
        -1799372.90858213, -1799904.33686236, -1799372.90858213,
        -1799904.33686236, -1799372.90858213, -1799904.33686236,
        -1738835.56317212, -1738835.56317212, -1738835.56317212,
        -1738835.56317212, -1738835.56317212, -1738835.56317212,
        -1720000.85175119, -1720000.85175119, -1720000.85175119,
        -1720000.85175119, -1720000.85175119, -1720000.85175119]),
 'mean_test_score': array([-1729837.21156422, -1738951.59056563, -1729837.21156422,
        -1738951.59056563, -1729837.21156422, -1738951.59056563,
        -1719539.6531303 , -1719539.6531303 , -1719539.6531303 ,
        -1719539.6531303 , -1719539.6531303 , -1719539.6531303 ,
        -1713679.68482721, -1713679.68482721, -1713679.68482721,
        -1713679.68482721, -1713679.68482721, -1713679.68482721,
        -1835011.68700556, -1840699.14221978, -1835011.68700556,
        -1840699.14221978, -1835011.68700556, -1840699.14221978,
        -1768018.30089906, -1768018.30089906, -1768018.30089906,
        -1768018.30089906, -1768018.30089906, -1768018.30089906,
        -1761672.82374997, -1761672.82374997, -1761672.82374997,
        -1761672.82374997, -1761672.82374997, -1761672.82374997]),
 'std_test_score': array([43807.45449451, 33879.95482044, 43807.45449451, 33879.95482044,
        43807.45449451, 33879.95482044, 22689.8290833 , 22689.8290833 ,
        22689.8290833 , 22689.8290833 , 22689.8290833 , 22689.8290833 ,
        34108.15949997, 34108.15949997, 34108.15949997, 34108.15949997,
        34108.15949997, 34108.15949997, 40033.66829227, 39586.16943828,
        40033.66829227, 39586.16943828, 40033.66829227, 39586.16943828,
        40139.7294364 , 40139.7294364 , 40139.7294364 , 40139.7294364 ,
        40139.7294364 , 40139.7294364 , 45821.11341498, 45821.11341498,
        45821.11341498, 45821.11341498, 45821.11341498, 45821.11341498]),
 'rank_test_score': array([13, 16, 13, 16, 13, 16,  7,  7,  7,  7,  7,  7,  1,  1,  1,  1,  1,
         1, 31, 34, 31, 34, 31, 34, 25, 25, 25, 25, 25, 25, 19, 19, 19, 19,
        19, 19])}

#Predict the model & see the  model results
opt_model = gridSearchCV.best_estimator_


predictions = (model.fit(x_train, y_train)).predict(x_test)
best_predictions = opt_model.predict(x_test)


print("Default Model\n------")
print("RMSE on testing data: {:.4f}".format(sqrt(mean_squared_error(y_test, predictions))))
print("r_2 on testing data: {:.4f}".format(r2_score(y_test, predictions)))
print("MAE on testing data: {:.4f}".format(mean_absolute_error(y_test, predictions)))
print("\nGrid Best Model\n------")
print("RMSE on testing data: {:.4f}".format(sqrt(mean_squared_error(y_test, best_predictions))))
print("r_2 on testing data: {:.4f}".format(r2_score(y_test, best_predictions)))
print("MAE on testing data: {:.4f}".format(mean_absolute_error(y_test, best_predictions)))

Default Model
------
RMSE on testing data: 3726731.7812
r_2 on testing data: 0.7886
MAE on testing data: 1618545.8519

Grid Best Model
------
RMSE on testing data: 3672946.1078
r_2 on testing data: 0.7947
MAE on testing data: 1553520.0283

#To get the feature names for feature importance
X=df.drop(['Fee_Money'],axis=1)

#Feature importance
feature_imp = pd.DataFrame(sorted(zip(opt_model.feature_importances_,X.columns)), columns=['Value','Feature'])

plt.figure(figsize=(20, 20))
sns.barplot(x="Value", y="Feature", data=feature_imp.sort_values(by="Value", ascending=False))
plt.title('LightGBM Feature Importance')
plt.tight_layout()
plt.show()
plt.savefig('lgbm_importances-01.png')

<Figure size 432x288 with 0 Axes>

#Feature importance with top 15 features
feature_imp2 = pd.DataFrame(sorted(zip(opt_model.feature_importances_,X.columns)), columns=['Value','Feature'])

plt.figure(figsize=(20, 10))
a=sns.barplot(x="Value", y="Feature", data=feature_imp2.sort_values(by="Value", ascending=False).head(20))
a.set_xlabel("Value",fontsize=20)
a.set_ylabel("Feature",fontsize=20)
plt.title('LightGBM Feature Importance')
plt.tight_layout()
plt.show()
plt.savefig('lgbm_importances-02.png')

<Figure size 432x288 with 0 Axes>

# Plot prediction & Values
lineStart = y_test.min() 
lineEnd = y_test.max()  

plt.figure()
plt.scatter(y_test, best_predictions, color = 'k', alpha=0.5)
plt.plot([lineStart, lineEnd], [lineStart, lineEnd], 'k-', color = 'r')
plt.xlim(lineStart, lineEnd)
plt.ylim(lineStart, lineEnd)
plt.title("Predictions vs Values on test dataset")
plt.xlabel("Values")
plt.ylabel("Predictions")
plt.show()

y_test

array([8200000, 5600000, 3000000, ...,  450000,  550000, 2470000],
      dtype=int64)

Keras

Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result as fast as possible is key to doing good research.

Keras is the high-level API of TensorFlow 2.0: an approchable, highly-productive interface for solving machine learning problems, with a focus on modern deep learning. It provides essential abstractions and building blocks for developing and shipping machine learning solutions with high iteration velocity.

Keras empowers engineers and researchers to take full advantage of the scalability and cross-platform capabilities of TensorFlow 2.0: you can run Keras on TPU or on large clusters of GPUs.

Source : Keras

# fill na with 0 
x_train2.fillna(0,inplace=True)
x_train2 = x_train2.replace([np.inf, -np.inf],0)
x_test2.fillna(0,inplace=True)
x_test2 = x_test2.replace([np.inf, -np.inf],0)

train_label = y_train2
test_label =  y_test2
train_features = x_train2
test_features = x_test2

# import the necessary packages
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import MaxPooling2D
from tensorflow.keras.layers import Activation
from tensorflow.keras.layers import Dropout
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Flatten
from tensorflow.keras.layers import Input
from tensorflow.keras.models import Model
def create_mlp(dim, regress=False):
    """ A function to train sequential Keras network
    Input: 
        Dimension of the dataset
    Output:
        Model to be trained
    """
    # define our MLP network
    model = Sequential()
    model.add(Dense(5000, input_dim=dim, activation="relu"))
    model.add(Dropout(0.2))
    model.add(Dense(2500, activation="relu"))
    model.add(Dropout(0.2))
    model.add(Dense(1000, activation="relu"))
    model.add(Dropout(0.2))
    model.add(Dense(500, activation="relu"))
    model.add(Dropout(0.2))
    model.add(Dense(250, activation="relu"))
    # check to see if the regression node should be added
    if regress:
        model.add(Dense(1, activation="linear"))
    # return our model
    return model

# # train the model
model = create_mlp(test_features.shape[1], regress=True)
model.compile(loss="mean_squared_error", optimizer='adam')
print("[INFO] training model...")
model.fit(x=train_features, y=train_label, 
    validation_split=0.2,
    epochs=25, batch_size=100)

[INFO] training model...
Epoch 1/25
54/54 [==============================] - 8s 157ms/step - loss: 35041237270528.0000 - val_loss: 33943818600448.0000
Epoch 2/25
54/54 [==============================] - 8s 155ms/step - loss: 21715289636864.0000 - val_loss: 17432988090368.0000
Epoch 3/25
54/54 [==============================] - 8s 155ms/step - loss: 24374606299136.0000 - val_loss: 18898518802432.0000
Epoch 4/25
54/54 [==============================] - 8s 155ms/step - loss: 20208630628352.0000 - val_loss: 14113268826112.0000
Epoch 5/25
54/54 [==============================] - 8s 155ms/step - loss: 21842811158528.0000 - val_loss: 14354304991232.0000
Epoch 6/25
54/54 [==============================] - 8s 156ms/step - loss: 23898152239104.0000 - val_loss: 15524380540928.0000
Epoch 7/25
54/54 [==============================] - 9s 159ms/step - loss: 28520231206912.0000 - val_loss: 20431098609664.0000
Epoch 8/25
54/54 [==============================] - 9s 158ms/step - loss: 24890497302528.0000 - val_loss: 20632569905152.0000
Epoch 9/25
54/54 [==============================] - 8s 156ms/step - loss: 24437474721792.0000 - val_loss: 17474377482240.0000
Epoch 10/25
54/54 [==============================] - 8s 155ms/step - loss: 28472116248576.0000 - val_loss: 41984181927936.0000
Epoch 11/25
54/54 [==============================] - 8s 156ms/step - loss: 25905709711360.0000 - val_loss: 22885393498112.0000
Epoch 12/25
54/54 [==============================] - 8s 156ms/step - loss: 28368911204352.0000 - val_loss: 21457824382976.0000
Epoch 13/25
54/54 [==============================] - 8s 155ms/step - loss: 24532192591872.0000 - val_loss: 17225914253312.0000
Epoch 14/25
54/54 [==============================] - 8s 156ms/step - loss: 25356499156992.0000 - val_loss: 32382512005120.0000
Epoch 15/25
54/54 [==============================] - 8s 156ms/step - loss: 27916349997056.0000 - val_loss: 28907969445888.0000
Epoch 16/25
54/54 [==============================] - 8s 156ms/step - loss: 22184284127232.0000 - val_loss: 23342392279040.0000
Epoch 17/25
54/54 [==============================] - 8s 156ms/step - loss: 27057742413824.0000 - val_loss: 17813064384512.0000
Epoch 18/25
54/54 [==============================] - 8s 157ms/step - loss: 23184912941056.0000 - val_loss: 15507284557824.0000
Epoch 19/25
54/54 [==============================] - 9s 159ms/step - loss: 23416033771520.0000 - val_loss: 16792128847872.0000
Epoch 20/25
54/54 [==============================] - 8s 156ms/step - loss: 23129709608960.0000 - val_loss: 16191949111296.0000
Epoch 21/25
54/54 [==============================] - 9s 158ms/step - loss: 21248568459264.0000 - val_loss: 17719950835712.0000
Epoch 22/25
54/54 [==============================] - 9s 159ms/step - loss: 20625068392448.0000 - val_loss: 18087147470848.0000
Epoch 23/25
54/54 [==============================] - 8s 156ms/step - loss: 23609357631488.0000 - val_loss: 16003918462976.0000
Epoch 24/25
54/54 [==============================] - 8s 156ms/step - loss: 22228418691072.0000 - val_loss: 18216636121088.0000
Epoch 25/25
54/54 [==============================] - 8s 157ms/step - loss: 19798039724032.0000 - val_loss: 14995342491648.0000

<tensorflow.python.keras.callbacks.History at 0x256d67ebca0>

# Model results for Keras
keras_preds = model.predict(test_features)
print("\nTensorflow Model\n------")
print("RMSE on testing data: {:.4f}".format(sqrt(mean_squared_error(y_test, keras_preds))))
print("r_2 on testing data: {:.4f}".format(r2_score(y_test, keras_preds)))
print("MAE on testing data: {:.4f}".format(mean_absolute_error(y_test, keras_preds)))

Tensorflow Model
------
RMSE on testing data: 3528093.1183
r_2 on testing data: 0.8106
MAE on testing data: 1568674.9879

lineStart = y_test.min() 
lineEnd = y_test.max()  

plt.figure()
plt.scatter(y_test, keras_preds, color = 'k', alpha=0.5)
plt.plot([lineStart, lineEnd], [lineStart, lineEnd], 'k-', color = 'r')
plt.xlim(lineStart, lineEnd)
plt.ylim(lineStart, lineEnd)
plt.title("Predictions vs Values on test dataset")
plt.xlabel("Values")
plt.ylabel("Predictions")
plt.show()

Results

• Keras make slightly better job predicting fee in test dataset compared to LightGBM ($R^2 = 0.810$ vs $R^2 = 0.794$)
• Both models underestimates the fees at high end.